LatexStuff
parent
ccec2c8994
commit
ce948e2dfd
|
|
@ -0,0 +1,34 @@
|
|||
\relax
|
||||
\@writefile{toc}{\contentsline {section}{\numberline {1}Introduction}{1}{}\protected@file@percent }
|
||||
\@writefile{toc}{\contentsline {section}{\numberline {2}Dataset}{1}{}\protected@file@percent }
|
||||
\@writefile{toc}{\contentsline {subsection}{\numberline {2.1}Data Augmentation}{1}{}\protected@file@percent }
|
||||
\newlabel{sec:augmentation}{{2.1}{1}{}{subsection.2.1}{}}
|
||||
\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces Sample images from the training dataset, showing the effect of data augmentation.}}{2}{}\protected@file@percent }
|
||||
\@writefile{toc}{\contentsline {section}{\numberline {3}Feature Extraction}{2}{}\protected@file@percent }
|
||||
\newlabel{sec:features}{{3}{2}{}{section.3}{}}
|
||||
\@writefile{toc}{\contentsline {section}{\numberline {4}Low-Level Features Models}{3}{}\protected@file@percent }
|
||||
\@writefile{toc}{\contentsline {subsection}{\numberline {4.1}Logistic Regression}{3}{}\protected@file@percent }
|
||||
\@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces Logistic regression training curves for different low level features.}}{3}{}\protected@file@percent }
|
||||
\providecommand*\caption@xref[2]{\@setref\relax\@undefined{#1}}
|
||||
\newlabel{fig:train_curves_color_logistic}{{2}{3}{}{figure.2}{}}
|
||||
\@writefile{lof}{\contentsline {figure}{\numberline {3}{\ignorespaces Summary of training (semi-transparent) and validation (solid) performance for different low-level feature combinations with logistic regression.}}{4}{}\protected@file@percent }
|
||||
\newlabel{fig:color_recap_logistic}{{3}{4}{}{figure.3}{}}
|
||||
\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces Visualization of the \emph {Histogram of Oriented Gradients} for a sample image. It's evident how HOG features perfectly capture shape and edge information, crucial for road sign classification.}}{4}{}\protected@file@percent }
|
||||
\newlabel{fig:hogging}{{4}{4}{}{figure.4}{}}
|
||||
\@writefile{toc}{\contentsline {subsection}{\numberline {4.2}Feature reduction}{4}{}\protected@file@percent }
|
||||
\@writefile{toc}{\contentsline {subsection}{\numberline {4.3}Grayscale}{5}{}\protected@file@percent }
|
||||
\@writefile{lof}{\contentsline {figure}{\numberline {5}{\ignorespaces Summary of training (semi-transparent) and validation (solid) performance for different low-level feature combinations with logistic regression on grayscale images.}}{5}{}\protected@file@percent }
|
||||
\newlabel{fig:grayscale_recap_logistic}{{5}{5}{}{figure.5}{}}
|
||||
\@writefile{toc}{\contentsline {subsection}{\numberline {4.4}Multi-Layer Perceptron}{5}{}\protected@file@percent }
|
||||
\@writefile{lof}{\contentsline {figure}{\numberline {6}{\ignorespaces Comparison of performance (both training and validation) on color and grayscale images with different MLPs.}}{6}{}\protected@file@percent }
|
||||
\newlabel{fig:recap_mlp}{{6}{6}{}{figure.6}{}}
|
||||
\@writefile{toc}{\contentsline {section}{\numberline {5}Convolutional Neural Network}{6}{}\protected@file@percent }
|
||||
\@writefile{lot}{\contentsline {table}{\numberline {1}{\ignorespaces CNN architecture. $C = 3$ for RGB, $C = 1$ for grayscale.}}{7}{}\protected@file@percent }
|
||||
\newlabel{tab:cnn_arch}{{1}{7}{}{table.1}{}}
|
||||
\@writefile{lof}{\contentsline {figure}{\numberline {7}{\ignorespaces CNN training curves for RGB images.}}{7}{}\protected@file@percent }
|
||||
\newlabel{fig:cnn_training}{{7}{7}{}{figure.7}{}}
|
||||
\@writefile{toc}{\contentsline {subsection}{\numberline {5.1}Activation Maps}{7}{}\protected@file@percent }
|
||||
\@writefile{lof}{\contentsline {figure}{\numberline {8}{\ignorespaces Comparison of first-layer activation maps for RGB and grayscale inputs. The RGB maps show stronger responses to color features, while the grayscale maps focus more on edges, shapes and contrast.}}{8}{}\protected@file@percent }
|
||||
\newlabel{fig:activation_maps}{{8}{8}{}{figure.8}{}}
|
||||
\@writefile{toc}{\contentsline {section}{\numberline {6}Conclusion}{8}{}\protected@file@percent }
|
||||
\gdef \@abspage@last{8}
|
||||
|
|
@ -0,0 +1,95 @@
|
|||
# Fdb version 4
|
||||
["pdflatex"] 1771726958.84777 "/home/porro/ml_temp/assignment_ml/LatexAssignement/Report.tex" "Report.pdf" "Report" 1771726959.8066 0
|
||||
"/etc/texmf/web2c/texmf.cnf" 1769451448.87747 475 c0e671620eb5563b2130f56340a5fde8 ""
|
||||
"/home/porro/ml_temp/assignment_ml/LatexAssignement/Report.tex" 1771726957.75303 19099 d80745ccace8531ac41daf186eeac518 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/map/fontname/texfonts.map" 1577235249 3524 cb3e574dea2d1052e39280babc910dc8 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/jknappen/ec/tcrm1095.tfm" 1136768653 1536 02c06700a42be0f5a28664c7273f82e7 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/cmextra/cmex7.tfm" 1246382020 1004 54797486969f23fa377b128694d548df ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/cmextra/cmex8.tfm" 1246382020 988 bdf658c3bfc2d96d3c8b02cfc1c94c20 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam10.tfm" 1246382020 916 f87d7c45f9c908e672703b83b72241a3 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam7.tfm" 1246382020 928 2dc8d444221b7a635bb58038579b861a ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm10.tfm" 1246382020 908 2921f8a10601f252058503cc6570e581 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm7.tfm" 1246382020 940 228d6584342e91276bf566bcf9716b83 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx10.tfm" 1136768653 1328 c834bbb027764024c09d3d2bf908b5f0 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx12.tfm" 1136768653 1324 c910af8c371558dc20f2d7822f66fe64 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx6.tfm" 1136768653 1344 8a0be4fe4d376203000810ad4dc81558 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx8.tfm" 1136768653 1332 1fde11373e221473104d6cc5993f046e ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmex10.tfm" 1136768653 992 662f679a0b3d2d53c1b94050fdaa3f50 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi10.tfm" 1136768653 1528 abec98dbc43e172678c11b3b9031252a ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi12.tfm" 1136768653 1524 4414a8315f39513458b80dfc63bff03a ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi6.tfm" 1136768653 1512 f21f83efb36853c0b70002322c1ab3ad ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi8.tfm" 1136768653 1520 eccf95517727cb11801f4f1aee3a21b4 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr10.tfm" 1136768653 1296 45809c5a464d5f32c8f98ba97c1bb47f ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr12.tfm" 1136768653 1288 655e228510b4c2a1abe905c368440826 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr17.tfm" 1136768653 1292 296a67155bdbfc32aa9c636f21e91433 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr6.tfm" 1136768653 1300 b62933e007d01cfd073f79b963c01526 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr8.tfm" 1136768653 1292 21c1c5bfeaebccffdb478fd231a0997d ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmsy10.tfm" 1136768653 1124 6c73e740cf17375f03eec0ee63599741 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmsy6.tfm" 1136768653 1116 933a60c408fc0a863a92debe84b2d294 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmsy8.tfm" 1136768653 1120 8b7d695260f3cff42e636090a8002094 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmti10.tfm" 1136768653 1480 aa8e34af0eb6a2941b776984cf1dfdc4 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmtt10.tfm" 1136768653 768 1321e9409b4137d6fb428ac9dc956269 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmbx10.pfb" 1248133631 34811 78b52f49e893bcba91bd7581cdc144c0 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmbx12.pfb" 1248133631 32080 340ef9bf63678554ee606688e7b5339d ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmex10.pfb" 1248133631 30251 6afa5cb1d0204815a708a080681d4674 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmmi10.pfb" 1248133631 36299 5f9df58c2139e7edcf37c8fca4bd384d ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmmi8.pfb" 1248133631 35469 70d41d2b9ea31d5d813066df7c99281c ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr10.pfb" 1248133631 35752 024fb6c41858982481f6968b5fc26508 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr12.pfb" 1248133631 32722 d7379af29a190c3f453aba36302ff5a9 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr17.pfb" 1248133631 32362 179c33bbf43f19adbb3825bb4e36e57a ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr8.pfb" 1248133631 32726 0a1aea6fcd6468ee2cf64d891f5c43c8 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmsy10.pfb" 1248133631 32569 5e5ddc8df908dea60932f3c484a54c0d ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmsy8.pfb" 1248133631 32626 4f5c1b83753b1dd3a97d1b399a005b4b ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmti10.pfb" 1248133631 37944 359e864bd06cde3b1cf57bb20757fb06 ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmtt10.pfb" 1248133631 31099 c85edf1dd5b9e826d67c9c7293b6786c ""
|
||||
"/usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/symbols/msbm10.pfb" 1248133631 34694 ad62b13721ee8eda1dcc8993c8bd7041 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/context/base/mkii/supp-pdf.mkii" 1461363279 71627 94eb9990bed73c364d7f53f960cc8c5b ""
|
||||
"/usr/share/texlive/texmf-dist/tex/generic/iftex/iftex.sty" 1734129479 7984 7dbb9280f03c0a315425f1b4f35d43ee ""
|
||||
"/usr/share/texlive/texmf-dist/tex/generic/iftex/ifvtex.sty" 1572645307 1057 525c2192b5febbd8c1f662c9468335bb ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsfonts/amsfonts.sty" 1359763108 5949 3f3fd50a8cc94c3d4cbf4fc66cd3df1c ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsfonts/amssymb.sty" 1359763108 13829 94730e64147574077f8ecfea9bb69af4 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsa.fd" 1359763108 961 6518c6525a34feb5e8250ffa91731cff ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsb.fd" 1359763108 961 d02606146ba5601b5645f987c92e6193 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsbsy.sty" 1717359999 2222 2166a1f7827be30ddc30434e5efcee1b ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsgen.sty" 1717359999 4173 d22509bc0c91281d991b2de7c88720dd ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsmath.sty" 1730928152 88370 c780f23aea0ece6add91e09b44dca2cd ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsopn.sty" 1717359999 4474 23ca1d3a79a57b405388059456d0a8df ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/amsmath/amstext.sty" 1717359999 2444 71618ea5f2377e33b04fb97afdd0eac2 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/base/article.cls" 1738182759 20144 63d8bacaf52e5abf4db3bc322373e1d4 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/base/size11.clo" 1738182759 8464 e73911cdcc738e82d6adccd28e654bb1 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/booktabs/booktabs.sty" 1579038678 6078 f1cb470c9199e7110a27851508ed7a5c ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/caption/caption.sty" 1696191071 56128 c2ccf1a29d78c33bc553880402e4fb9a ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/caption/caption3.sty" 1696191071 72619 ee90b6612147680fd73c3b1406a74245 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/caption/subcaption.sty" 1690576852 12494 0c0cdb824278a4d51cefeb2e79901315 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/epstopdf-pkg/epstopdf-base.sty" 1579991033 13886 d1306dcf79a944f6988e688c1785f9ce ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/geometry/geometry.sty" 1578002852 41601 9cf6c5257b1bc7af01a58859749dd37a ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/graphics-cfg/graphics.cfg" 1465944070 1224 978390e9c2234eab29404bc21b268d1e ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/graphics-def/pdftex.def" 1713382759 19440 9da9dcbb27470349a580fca7372d454b ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/graphics/graphics.sty" 1730496337 18363 dee506cb8d56825d8a4d020f5d5f8704 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/graphics/graphicx.sty" 1717359999 8010 6f2ad8c2b2ffbd607af6475441c7b5e4 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/graphics/keyval.sty" 1717359999 2671 70891d50dac933918b827d326687c6e8 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/graphics/trig.sty" 1717359999 4023 2c9f39712cf7b43d3eb93a8bbd5c8f67 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/l3backend/l3backend-pdftex.def" 1716410060 29785 9f93ab201fe5dd053afcc6c1bcf7d266 ""
|
||||
"/usr/share/texlive/texmf-dist/tex/latex/latexconfig/epstopdf-sys.cfg" 1279039959 678 4792914a8f45be57bb98413425e4c7af ""
|
||||
"/usr/share/texlive/texmf-dist/web2c/texmf.cnf" 1741904018 41538 c016915c1d51223b6dbbfe27341748a8 ""
|
||||
"/usr/share/texmf/fonts/enc/dvips/cm-super/cm-super-ts1.enc" 1636152094 2900 1537cc8184ad1792082cd229ecc269f4 ""
|
||||
"/usr/share/texmf/fonts/type1/public/cm-super/sfrm1095.pfb" 1769451457.78157 145929 f25e56369a345c4ff583b067cd87ce8e ""
|
||||
"/usr/share/texmf/web2c/texmf.cnf" 1741904018 41538 c016915c1d51223b6dbbfe27341748a8 ""
|
||||
"/var/lib/texmf/fonts/map/pdftex/updmap/pdftex.map" 1769451462 5467255 9a64d1b40e0b893fc5588ecce9d8accf ""
|
||||
"/var/lib/texmf/web2c/pdftex/pdflatex.fmt" 1769451495 3348541 ea3e464b5d2356c23b6a83557c5a7db9 ""
|
||||
"Report.aux" 1771726959.76107 3883 3c3a303c2ed93a98b13359fb4c27a130 "pdflatex"
|
||||
"Report.tex" 1771726957.75303 19099 d80745ccace8531ac41daf186eeac518 ""
|
||||
"imgs/cnn_activation_maps.png" 1771726599.45035 893283 f39ea2a5c3f3ca145580a9deb42c349d ""
|
||||
"imgs/cnn_train_color.png" 1771725909.17683 72816 12b9318a7036f90c29c1da720c60bd5b ""
|
||||
"imgs/edge_dir_train.png" 1771719852.64623 89331 0ffb00e3715d5d1d25f59e0e6c330a73 ""
|
||||
"imgs/hog_train.png" 1771719875.65041 31168 97068e141e085db9a5faa76491f51480 ""
|
||||
"imgs/hogging.png" 1771721107.22331 120154 2ffca50ac360aafca2e88b09d1b30551 ""
|
||||
"imgs/logistic_color_summary.png" 1771719911.04668 61445 2e98039025369aa2710e0578cae749d1 ""
|
||||
"imgs/logistic_gray_summary.png" 1771722012.03485 59951 cf1d8f1b5adf4a5aa5487f1881ed91ac ""
|
||||
"imgs/mlp_no_hog_summary.png" 1771722988.85654 53914 88ee8392f4c0c7c477cc351ff1babea7 ""
|
||||
"imgs/train_augmented.png" 1771711565.82367 701930 75ae07d1e848c95b0efc0b5535abf878 ""
|
||||
(generated)
|
||||
"Report.aux"
|
||||
"Report.log"
|
||||
"Report.pdf"
|
||||
(rewritten before read)
|
||||
|
|
@ -0,0 +1,165 @@
|
|||
PWD /home/porro/ml_temp/assignment_ml/LatexAssignement
|
||||
INPUT /etc/texmf/web2c/texmf.cnf
|
||||
INPUT /usr/share/texmf/web2c/texmf.cnf
|
||||
INPUT /usr/share/texlive/texmf-dist/web2c/texmf.cnf
|
||||
INPUT /var/lib/texmf/web2c/pdftex/pdflatex.fmt
|
||||
INPUT /home/porro/ml_temp/assignment_ml/LatexAssignement/Report.tex
|
||||
OUTPUT Report.log
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/base/article.cls
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/base/article.cls
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/base/size11.clo
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/base/size11.clo
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/base/size11.clo
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/map/fontname/texfonts.map
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/geometry/geometry.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/geometry/geometry.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics/keyval.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics/keyval.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/generic/iftex/ifvtex.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/generic/iftex/ifvtex.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/generic/iftex/iftex.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/generic/iftex/iftex.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics/graphicx.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics/graphicx.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics/graphics.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics/graphics.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics/trig.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics/trig.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics-cfg/graphics.cfg
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics-cfg/graphics.cfg
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics-cfg/graphics.cfg
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics-def/pdftex.def
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics-def/pdftex.def
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/graphics-def/pdftex.def
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amsmath.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amsmath.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amsopn.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amstext.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amstext.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amsgen.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amsgen.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amsbsy.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amsbsy.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsmath/amsopn.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/amssymb.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/amssymb.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/amsfonts.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/amsfonts.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/booktabs/booktabs.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/booktabs/booktabs.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/caption/subcaption.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/caption/subcaption.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/caption/caption.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/caption/caption.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/caption/caption3.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/caption/caption3.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/l3backend/l3backend-pdftex.def
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/l3backend/l3backend-pdftex.def
|
||||
INPUT ./Report.aux
|
||||
INPUT ./Report.aux
|
||||
INPUT Report.aux
|
||||
OUTPUT Report.aux
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/context/base/mkii/supp-pdf.mkii
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/context/base/mkii/supp-pdf.mkii
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/context/base/mkii/supp-pdf.mkii
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/epstopdf-pkg/epstopdf-base.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/epstopdf-pkg/epstopdf-base.sty
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/latexconfig/epstopdf-sys.cfg
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/latexconfig/epstopdf-sys.cfg
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/latexconfig/epstopdf-sys.cfg
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr17.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmti10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr12.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr8.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr6.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi12.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi8.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi6.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmsy10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmsy8.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmsy6.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmex10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/cmextra/cmex8.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/cmextra/cmex7.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsa.fd
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsa.fd
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsa.fd
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam7.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsb.fd
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsb.fd
|
||||
INPUT /usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsb.fd
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm7.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr12.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx12.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/jknappen/ec/tcrm1095.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx12.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmsy10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmex10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msam10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/amsfonts/symbols/msbm10.tfm
|
||||
OUTPUT Report.pdf
|
||||
INPUT /var/lib/texmf/fonts/map/pdftex/updmap/pdftex.map
|
||||
INPUT /usr/share/texmf/fonts/enc/dvips/cm-super/cm-super-ts1.enc
|
||||
INPUT ./imgs/train_augmented.png
|
||||
INPUT ./imgs/train_augmented.png
|
||||
INPUT ./imgs/train_augmented.png
|
||||
INPUT ./imgs/train_augmented.png
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmtt10.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx8.tfm
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmbx6.tfm
|
||||
INPUT ./imgs/edge_dir_train.png
|
||||
INPUT ./imgs/edge_dir_train.png
|
||||
INPUT ./imgs/edge_dir_train.png
|
||||
INPUT ./imgs/edge_dir_train.png
|
||||
INPUT ./imgs/hog_train.png
|
||||
INPUT ./imgs/hog_train.png
|
||||
INPUT ./imgs/hog_train.png
|
||||
INPUT ./imgs/hog_train.png
|
||||
INPUT ./imgs/logistic_color_summary.png
|
||||
INPUT ./imgs/logistic_color_summary.png
|
||||
INPUT ./imgs/logistic_color_summary.png
|
||||
INPUT ./imgs/logistic_color_summary.png
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmti10.tfm
|
||||
INPUT ./imgs/hogging.png
|
||||
INPUT ./imgs/hogging.png
|
||||
INPUT ./imgs/hogging.png
|
||||
INPUT ./imgs/hogging.png
|
||||
INPUT ./imgs/logistic_gray_summary.png
|
||||
INPUT ./imgs/logistic_gray_summary.png
|
||||
INPUT ./imgs/logistic_gray_summary.png
|
||||
INPUT ./imgs/logistic_gray_summary.png
|
||||
INPUT ./imgs/mlp_no_hog_summary.png
|
||||
INPUT ./imgs/mlp_no_hog_summary.png
|
||||
INPUT ./imgs/mlp_no_hog_summary.png
|
||||
INPUT ./imgs/mlp_no_hog_summary.png
|
||||
INPUT ./imgs/cnn_train_color.png
|
||||
INPUT ./imgs/cnn_train_color.png
|
||||
INPUT ./imgs/cnn_train_color.png
|
||||
INPUT ./imgs/cnn_train_color.png
|
||||
INPUT ./imgs/cnn_activation_maps.png
|
||||
INPUT ./imgs/cnn_activation_maps.png
|
||||
INPUT ./imgs/cnn_activation_maps.png
|
||||
INPUT ./imgs/cnn_activation_maps.png
|
||||
INPUT Report.aux
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmbx10.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmbx12.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmex10.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmmi10.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmmi8.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr10.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr12.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr17.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr8.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmsy10.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmsy8.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmti10.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmtt10.pfb
|
||||
INPUT /usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/symbols/msbm10.pfb
|
||||
INPUT /usr/share/texmf/fonts/type1/public/cm-super/sfrm1095.pfb
|
||||
|
|
@ -0,0 +1,366 @@
|
|||
This is pdfTeX, Version 3.141592653-2.6-1.40.26 (TeX Live 2025/dev/Debian) (preloaded format=pdflatex 2026.1.26) 22 FEB 2026 03:22
|
||||
entering extended mode
|
||||
restricted \write18 enabled.
|
||||
file:line:error style messages enabled.
|
||||
%&-line parsing enabled.
|
||||
**/home/porro/ml_temp/assignment_ml/LatexAssignement/Report.tex
|
||||
(/home/porro/ml_temp/assignment_ml/LatexAssignement/Report.tex
|
||||
LaTeX2e <2024-11-01> patch level 2
|
||||
L3 programming layer <2025-01-18>
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/base/article.cls
|
||||
Document Class: article 2024/06/29 v1.4n Standard LaTeX document class
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/base/size11.clo
|
||||
File: size11.clo 2024/06/29 v1.4n Standard LaTeX file (size option)
|
||||
)
|
||||
\c@part=\count196
|
||||
\c@section=\count197
|
||||
\c@subsection=\count198
|
||||
\c@subsubsection=\count199
|
||||
\c@paragraph=\count266
|
||||
\c@subparagraph=\count267
|
||||
\c@figure=\count268
|
||||
\c@table=\count269
|
||||
\abovecaptionskip=\skip49
|
||||
\belowcaptionskip=\skip50
|
||||
\bibindent=\dimen141
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/geometry/geometry.sty
|
||||
Package: geometry 2020/01/02 v5.9 Page Geometry
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/graphics/keyval.sty
|
||||
Package: keyval 2022/05/29 v1.15 key=value parser (DPC)
|
||||
\KV@toks@=\toks17
|
||||
) (/usr/share/texlive/texmf-dist/tex/generic/iftex/ifvtex.sty
|
||||
Package: ifvtex 2019/10/25 v1.7 ifvtex legacy package. Use iftex instead.
|
||||
(/usr/share/texlive/texmf-dist/tex/generic/iftex/iftex.sty
|
||||
Package: iftex 2024/12/12 v1.0g TeX engine tests
|
||||
))
|
||||
\Gm@cnth=\count270
|
||||
\Gm@cntv=\count271
|
||||
\c@Gm@tempcnt=\count272
|
||||
\Gm@bindingoffset=\dimen142
|
||||
\Gm@wd@mp=\dimen143
|
||||
\Gm@odd@mp=\dimen144
|
||||
\Gm@even@mp=\dimen145
|
||||
\Gm@layoutwidth=\dimen146
|
||||
\Gm@layoutheight=\dimen147
|
||||
\Gm@layouthoffset=\dimen148
|
||||
\Gm@layoutvoffset=\dimen149
|
||||
\Gm@dimlist=\toks18
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/graphics/graphicx.sty
|
||||
Package: graphicx 2021/09/16 v1.2d Enhanced LaTeX Graphics (DPC,SPQR)
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/graphics/graphics.sty
|
||||
Package: graphics 2024/08/06 v1.4g Standard LaTeX Graphics (DPC,SPQR)
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/graphics/trig.sty
|
||||
Package: trig 2023/12/02 v1.11 sin cos tan (DPC)
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/graphics-cfg/graphics.cfg
|
||||
File: graphics.cfg 2016/06/04 v1.11 sample graphics configuration
|
||||
)
|
||||
Package graphics Info: Driver file: pdftex.def on input line 106.
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/graphics-def/pdftex.def
|
||||
File: pdftex.def 2024/04/13 v1.2c Graphics/color driver for pdftex
|
||||
))
|
||||
\Gin@req@height=\dimen150
|
||||
\Gin@req@width=\dimen151
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsmath.sty
|
||||
Package: amsmath 2024/11/05 v2.17t AMS math features
|
||||
\@mathmargin=\skip51
|
||||
|
||||
For additional information on amsmath, use the `?' option.
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/amsmath/amstext.sty
|
||||
Package: amstext 2021/08/26 v2.01 AMS text
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsgen.sty
|
||||
File: amsgen.sty 1999/11/30 v2.0 generic functions
|
||||
\@emptytoks=\toks19
|
||||
\ex@=\dimen152
|
||||
)) (/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsbsy.sty
|
||||
Package: amsbsy 1999/11/29 v1.2d Bold Symbols
|
||||
\pmbraise@=\dimen153
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsopn.sty
|
||||
Package: amsopn 2022/04/08 v2.04 operator names
|
||||
)
|
||||
\inf@bad=\count273
|
||||
LaTeX Info: Redefining \frac on input line 233.
|
||||
\uproot@=\count274
|
||||
\leftroot@=\count275
|
||||
LaTeX Info: Redefining \overline on input line 398.
|
||||
LaTeX Info: Redefining \colon on input line 409.
|
||||
\classnum@=\count276
|
||||
\DOTSCASE@=\count277
|
||||
LaTeX Info: Redefining \ldots on input line 495.
|
||||
LaTeX Info: Redefining \dots on input line 498.
|
||||
LaTeX Info: Redefining \cdots on input line 619.
|
||||
\Mathstrutbox@=\box52
|
||||
\strutbox@=\box53
|
||||
LaTeX Info: Redefining \big on input line 721.
|
||||
LaTeX Info: Redefining \Big on input line 722.
|
||||
LaTeX Info: Redefining \bigg on input line 723.
|
||||
LaTeX Info: Redefining \Bigg on input line 724.
|
||||
\big@size=\dimen154
|
||||
LaTeX Font Info: Redeclaring font encoding OML on input line 742.
|
||||
LaTeX Font Info: Redeclaring font encoding OMS on input line 743.
|
||||
\macc@depth=\count278
|
||||
LaTeX Info: Redefining \bmod on input line 904.
|
||||
LaTeX Info: Redefining \pmod on input line 909.
|
||||
LaTeX Info: Redefining \smash on input line 939.
|
||||
LaTeX Info: Redefining \relbar on input line 969.
|
||||
LaTeX Info: Redefining \Relbar on input line 970.
|
||||
\c@MaxMatrixCols=\count279
|
||||
\dotsspace@=\muskip17
|
||||
\c@parentequation=\count280
|
||||
\dspbrk@lvl=\count281
|
||||
\tag@help=\toks20
|
||||
\row@=\count282
|
||||
\column@=\count283
|
||||
\maxfields@=\count284
|
||||
\andhelp@=\toks21
|
||||
\eqnshift@=\dimen155
|
||||
\alignsep@=\dimen156
|
||||
\tagshift@=\dimen157
|
||||
\tagwidth@=\dimen158
|
||||
\totwidth@=\dimen159
|
||||
\lineht@=\dimen160
|
||||
\@envbody=\toks22
|
||||
\multlinegap=\skip52
|
||||
\multlinetaggap=\skip53
|
||||
\mathdisplay@stack=\toks23
|
||||
LaTeX Info: Redefining \[ on input line 2953.
|
||||
LaTeX Info: Redefining \] on input line 2954.
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/amsfonts/amssymb.sty
|
||||
Package: amssymb 2013/01/14 v3.01 AMS font symbols
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/amsfonts/amsfonts.sty
|
||||
Package: amsfonts 2013/01/14 v3.01 Basic AMSFonts support
|
||||
\symAMSa=\mathgroup4
|
||||
\symAMSb=\mathgroup5
|
||||
LaTeX Font Info: Redeclaring math symbol \hbar on input line 98.
|
||||
LaTeX Font Info: Overwriting math alphabet `\mathfrak' in version `bold'
|
||||
(Font) U/euf/m/n --> U/euf/b/n on input line 106.
|
||||
)) (/usr/share/texlive/texmf-dist/tex/latex/booktabs/booktabs.sty
|
||||
Package: booktabs 2020/01/12 v1.61803398 Publication quality tables
|
||||
\heavyrulewidth=\dimen161
|
||||
\lightrulewidth=\dimen162
|
||||
\cmidrulewidth=\dimen163
|
||||
\belowrulesep=\dimen164
|
||||
\belowbottomsep=\dimen165
|
||||
\aboverulesep=\dimen166
|
||||
\abovetopsep=\dimen167
|
||||
\cmidrulesep=\dimen168
|
||||
\cmidrulekern=\dimen169
|
||||
\defaultaddspace=\dimen170
|
||||
\@cmidla=\count285
|
||||
\@cmidlb=\count286
|
||||
\@aboverulesep=\dimen171
|
||||
\@belowrulesep=\dimen172
|
||||
\@thisruleclass=\count287
|
||||
\@lastruleclass=\count288
|
||||
\@thisrulewidth=\dimen173
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/caption/subcaption.sty
|
||||
Package: subcaption 2023/07/28 v1.6b Sub-captions (AR)
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/caption/caption.sty
|
||||
Package: caption 2023/08/05 v3.6o Customizing captions (AR)
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/caption/caption3.sty
|
||||
Package: caption3 2023/07/31 v2.4d caption3 kernel (AR)
|
||||
\caption@tempdima=\dimen174
|
||||
\captionmargin=\dimen175
|
||||
\caption@leftmargin=\dimen176
|
||||
\caption@rightmargin=\dimen177
|
||||
\caption@width=\dimen178
|
||||
\caption@indent=\dimen179
|
||||
\caption@parindent=\dimen180
|
||||
\caption@hangindent=\dimen181
|
||||
Package caption Info: Standard document class detected.
|
||||
)
|
||||
\c@caption@flags=\count289
|
||||
\c@continuedfloat=\count290
|
||||
)
|
||||
Package caption Info: New subtype `subfigure' on input line 238.
|
||||
\c@subfigure=\count291
|
||||
Package caption Info: New subtype `subtable' on input line 238.
|
||||
\c@subtable=\count292
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/l3backend/l3backend-pdftex.def
|
||||
File: l3backend-pdftex.def 2024-05-08 L3 backend support: PDF output (pdfTeX)
|
||||
\l__color_backend_stack_int=\count293
|
||||
\l__pdf_internal_box=\box54
|
||||
) (./Report.aux)
|
||||
\openout1 = `Report.aux'.
|
||||
|
||||
LaTeX Font Info: Checking defaults for OML/cmm/m/it on input line 18.
|
||||
LaTeX Font Info: ... okay on input line 18.
|
||||
LaTeX Font Info: Checking defaults for OMS/cmsy/m/n on input line 18.
|
||||
LaTeX Font Info: ... okay on input line 18.
|
||||
LaTeX Font Info: Checking defaults for OT1/cmr/m/n on input line 18.
|
||||
LaTeX Font Info: ... okay on input line 18.
|
||||
LaTeX Font Info: Checking defaults for T1/cmr/m/n on input line 18.
|
||||
LaTeX Font Info: ... okay on input line 18.
|
||||
LaTeX Font Info: Checking defaults for TS1/cmr/m/n on input line 18.
|
||||
LaTeX Font Info: ... okay on input line 18.
|
||||
LaTeX Font Info: Checking defaults for OMX/cmex/m/n on input line 18.
|
||||
LaTeX Font Info: ... okay on input line 18.
|
||||
LaTeX Font Info: Checking defaults for U/cmr/m/n on input line 18.
|
||||
LaTeX Font Info: ... okay on input line 18.
|
||||
|
||||
*geometry* driver: auto-detecting
|
||||
*geometry* detected driver: pdftex
|
||||
*geometry* verbose mode - [ preamble ] result:
|
||||
* driver: pdftex
|
||||
* paper: a4paper
|
||||
* layout: <same size as paper>
|
||||
* layoutoffset:(h,v)=(0.0pt,0.0pt)
|
||||
* modes:
|
||||
* h-part:(L,W,R)=(76.82234pt, 443.86319pt, 76.82234pt)
|
||||
* v-part:(T,H,B)=(76.82234pt, 691.40216pt, 76.82234pt)
|
||||
* \paperwidth=597.50787pt
|
||||
* \paperheight=845.04684pt
|
||||
* \textwidth=443.86319pt
|
||||
* \textheight=691.40216pt
|
||||
* \oddsidemargin=4.55235pt
|
||||
* \evensidemargin=4.55235pt
|
||||
* \topmargin=-32.44765pt
|
||||
* \headheight=12.0pt
|
||||
* \headsep=25.0pt
|
||||
* \topskip=11.0pt
|
||||
* \footskip=30.0pt
|
||||
* \marginparwidth=50.0pt
|
||||
* \marginparsep=10.0pt
|
||||
* \columnsep=10.0pt
|
||||
* \skip\footins=10.0pt plus 4.0pt minus 2.0pt
|
||||
* \hoffset=0.0pt
|
||||
* \voffset=0.0pt
|
||||
* \mag=1000
|
||||
* \@twocolumnfalse
|
||||
* \@twosidefalse
|
||||
* \@mparswitchfalse
|
||||
* \@reversemarginfalse
|
||||
* (1in=72.27pt=25.4mm, 1cm=28.453pt)
|
||||
|
||||
(/usr/share/texlive/texmf-dist/tex/context/base/mkii/supp-pdf.mkii
|
||||
[Loading MPS to PDF converter (version 2006.09.02).]
|
||||
\scratchcounter=\count294
|
||||
\scratchdimen=\dimen182
|
||||
\scratchbox=\box55
|
||||
\nofMPsegments=\count295
|
||||
\nofMParguments=\count296
|
||||
\everyMPshowfont=\toks24
|
||||
\MPscratchCnt=\count297
|
||||
\MPscratchDim=\dimen183
|
||||
\MPnumerator=\count298
|
||||
\makeMPintoPDFobject=\count299
|
||||
\everyMPtoPDFconversion=\toks25
|
||||
) (/usr/share/texlive/texmf-dist/tex/latex/epstopdf-pkg/epstopdf-base.sty
|
||||
Package: epstopdf-base 2020-01-24 v2.11 Base part for package epstopdf
|
||||
Package epstopdf-base Info: Redefining graphics rule for `.eps' on input line 485.
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/latexconfig/epstopdf-sys.cfg
|
||||
File: epstopdf-sys.cfg 2010/07/13 v1.3 Configuration of (r)epstopdf for TeX Live
|
||||
))
|
||||
Package caption Info: Begin \AtBeginDocument code.
|
||||
Package caption Info: End \AtBeginDocument code.
|
||||
LaTeX Font Info: Trying to load font information for U+msa on input line 19.
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsa.fd
|
||||
File: umsa.fd 2013/01/14 v3.01 AMS symbols A
|
||||
)
|
||||
LaTeX Font Info: Trying to load font information for U+msb on input line 19.
|
||||
(/usr/share/texlive/texmf-dist/tex/latex/amsfonts/umsb.fd
|
||||
File: umsb.fd 2013/01/14 v3.01 AMS symbols B
|
||||
)
|
||||
|
||||
[1
|
||||
|
||||
{/var/lib/texmf/fonts/map/pdftex/updmap/pdftex.map}{/usr/share/texmf/fonts/enc/dvips/cm-super/cm-super-ts1.enc}]
|
||||
<imgs/train_augmented.png, id=14, 372.55185pt x 193.6836pt>
|
||||
File: imgs/train_augmented.png Graphic file (type png)
|
||||
<use imgs/train_augmented.png>
|
||||
Package pdftex.def Info: imgs/train_augmented.png used on input line 42.
|
||||
(pdftex.def) Requested size: 332.89738pt x 173.0753pt.
|
||||
|
||||
|
||||
[2 <./imgs/train_augmented.png>]
|
||||
<imgs/edge_dir_train.png, id=24, 417.7206pt x 268.8444pt>
|
||||
File: imgs/edge_dir_train.png Graphic file (type png)
|
||||
<use imgs/edge_dir_train.png>
|
||||
Package pdftex.def Info: imgs/edge_dir_train.png used on input line 86.
|
||||
(pdftex.def) Requested size: 213.05243pt x 137.11703pt.
|
||||
<imgs/hog_train.png, id=25, 417.7206pt x 268.8444pt>
|
||||
File: imgs/hog_train.png Graphic file (type png)
|
||||
<use imgs/hog_train.png>
|
||||
Package pdftex.def Info: imgs/hog_train.png used on input line 92.
|
||||
(pdftex.def) Requested size: 213.05243pt x 137.11703pt.
|
||||
<imgs/logistic_color_summary.png, id=26, 418.2024pt x 254.1495pt>
|
||||
File: imgs/logistic_color_summary.png Graphic file (type png)
|
||||
<use imgs/logistic_color_summary.png>
|
||||
Package pdftex.def Info: imgs/logistic_color_summary.png used on input line 101.
|
||||
(pdftex.def) Requested size: 399.47415pt x 242.77469pt.
|
||||
|
||||
|
||||
LaTeX Warning: `!h' float specifier changed to `!ht'.
|
||||
|
||||
<imgs/hogging.png, id=27, 354.3639pt x 180.4341pt>
|
||||
File: imgs/hogging.png Graphic file (type png)
|
||||
<use imgs/hogging.png>
|
||||
Package pdftex.def Info: imgs/hogging.png used on input line 110.
|
||||
(pdftex.def) Requested size: 332.89738pt x 169.51169pt.
|
||||
|
||||
LaTeX Warning: `!h' float specifier changed to `!ht'.
|
||||
|
||||
|
||||
|
||||
[3 <./imgs/edge_dir_train.png> <./imgs/hog_train.png>]
|
||||
|
||||
[4 <./imgs/logistic_color_summary.png> <./imgs/hogging.png>]
|
||||
<imgs/logistic_gray_summary.png, id=41, 418.2024pt x 254.1495pt>
|
||||
File: imgs/logistic_gray_summary.png Graphic file (type png)
|
||||
<use imgs/logistic_gray_summary.png>
|
||||
Package pdftex.def Info: imgs/logistic_gray_summary.png used on input line 129.
|
||||
(pdftex.def) Requested size: 399.47415pt x 242.77469pt.
|
||||
|
||||
|
||||
[5 <./imgs/logistic_gray_summary.png>]
|
||||
<imgs/mlp_no_hog_summary.png, id=46, 418.2024pt x 254.1495pt>
|
||||
File: imgs/mlp_no_hog_summary.png Graphic file (type png)
|
||||
<use imgs/mlp_no_hog_summary.png>
|
||||
Package pdftex.def Info: imgs/mlp_no_hog_summary.png used on input line 145.
|
||||
(pdftex.def) Requested size: 399.47415pt x 242.77469pt.
|
||||
|
||||
|
||||
LaTeX Warning: `!h' float specifier changed to `!ht'.
|
||||
|
||||
|
||||
|
||||
[6 <./imgs/mlp_no_hog_summary.png>]
|
||||
<imgs/cnn_train_color.png, id=51, 417.7206pt x 268.8444pt>
|
||||
File: imgs/cnn_train_color.png Graphic file (type png)
|
||||
<use imgs/cnn_train_color.png>
|
||||
Package pdftex.def Info: imgs/cnn_train_color.png used on input line 180.
|
||||
(pdftex.def) Requested size: 355.0919pt x 228.53523pt.
|
||||
<imgs/cnn_activation_maps.png, id=52, 781.60005pt x 273.9033pt>
|
||||
File: imgs/cnn_activation_maps.png Graphic file (type png)
|
||||
<use imgs/cnn_activation_maps.png>
|
||||
Package pdftex.def Info: imgs/cnn_activation_maps.png used on input line 190.
|
||||
(pdftex.def) Requested size: 443.86319pt x 155.54555pt.
|
||||
|
||||
|
||||
LaTeX Warning: `!h' float specifier changed to `!ht'.
|
||||
|
||||
|
||||
|
||||
[7 <./imgs/cnn_train_color.png>]
|
||||
|
||||
[8 <./imgs/cnn_activation_maps.png>] (./Report.aux)
|
||||
***********
|
||||
LaTeX2e <2024-11-01> patch level 2
|
||||
L3 programming layer <2025-01-18>
|
||||
***********
|
||||
)
|
||||
Here is how much of TeX's memory you used:
|
||||
4753 strings out of 473197
|
||||
77212 string characters out of 5718605
|
||||
470950 words of memory out of 5000000
|
||||
27975 multiletter control sequences out of 15000+600000
|
||||
568371 words of font info for 71 fonts, out of 8000000 for 9000
|
||||
1141 hyphenation exceptions out of 8191
|
||||
67i,10n,77p,1380b,490s stack positions out of 10000i,1000n,20000p,200000b,200000s
|
||||
</usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmbx10.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmbx12.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmex10.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmmi10.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmmi8.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr10.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr12.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr17.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmr8.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmsy10.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmsy8.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmti10.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/cm/cmtt10.pfb></usr/share/texlive/texmf-dist/fonts/type1/public/amsfonts/symbols/msbm10.pfb></usr/share/texmf/fonts/type1/public/cm-super/sfrm1095.pfb>
|
||||
Output written on Report.pdf (8 pages, 2463410 bytes).
|
||||
PDF statistics:
|
||||
126 PDF objects out of 1000 (max. 8388607)
|
||||
67 compressed objects within 1 object stream
|
||||
0 named destinations out of 1000 (max. 500000)
|
||||
46 words of extra memory for PDF output out of 10000 (max. 10000000)
|
||||
|
||||
Binary file not shown.
Binary file not shown.
|
|
@ -0,0 +1,201 @@
|
|||
\documentclass[11pt, a4paper]{article}
|
||||
|
||||
\usepackage[a4paper,left=2.7cm,right=2.7cm,top=2.7cm,bottom=2.7cm]{geometry}
|
||||
\usepackage{graphicx}
|
||||
\usepackage{amsmath}
|
||||
\usepackage{amssymb}
|
||||
\usepackage{booktabs}
|
||||
|
||||
\usepackage{subcaption}
|
||||
|
||||
|
||||
\graphicspath{{imgs/}}
|
||||
|
||||
\title{Road Signs Classification \\ [1ex] \small\emph{Machine Learning Course - Programming Assignment}}
|
||||
\author{Roberto Mastrofrancesco}
|
||||
\date{10th February 2026}
|
||||
|
||||
\begin{document}
|
||||
\maketitle
|
||||
|
||||
\section{Introduction}
|
||||
Road sign recognition is a critical component of autonomous driving systems, enabling vehicles to understand and respond to traffic signs effectively. The objective of this report is to train different classification models to correctly classify road signs from a given dataset. Different models of varying complexity have been explored and evaluated, implementing proper feature extraction techniques where necessary.
|
||||
|
||||
The notebook from which the results are obtained is run on my personal computer with the following specifications: Intel Core i7-8700K CPU, 32GB RAM, and NVIDIA GeForce GTX 1080Ti GPU.
|
||||
|
||||
\section{Dataset}
|
||||
The dataset comprises 1088 color images of 200x200 pixels divided into 20 distinct road sign classes. Each class contains a set of training samples and 10 test samples, with the number of training images varying across classes. To proceed with the assignment, an additional small validation set was created from the training samples, obtaining the following configuration:
|
||||
\begin{itemize}
|
||||
\item Training set: 788 images (not equally distributed across classes due to the original dataset being imbalanced).
|
||||
\item Validation set: 100 images, 5 per class; it has been constructed by randomly selecting 5 images from each class of the original training set.
|
||||
\item Test set: 200 images, 10 per class (as provided in the original dataset).
|
||||
\end{itemize}
|
||||
|
||||
\subsection{Data Augmentation}\label{sec:augmentation}
|
||||
Due to the relatively small number of training samples, data augmentation techniques were applied to increase the diversity of the training data and improve model generalization. In particular, transformations able to modify the images while preserving the recognizability of the road signs, such as random low-angle rotations ($<10^\circ$), horizontal flips and small brightness adjustments, were implemented.
|
||||
|
||||
Data augmentation was also applied when extracting low-level features (section \ref{sec:features}): although augmentation was not re-applied on the fly during training, it still increased the diversity of the training set. This design choice was made to allow consistent standardization of the extracted features; if augmentation were applied on the fly, features would differ at each epoch, making standardization inconsistent across epochs. Moreover, since low-level features were only used with relatively small models (logistic regression and MLPs with few hidden layers, section [HERE]), on-the-fly augmentation would not have provided a significant performance benefit while being considerably more computationally expensive. For the CNN (section [HERE]), where the higher number of parameters demands stronger regularization, the standard on-the-fly augmentation procedure was followed.
|
||||
|
||||
|
||||
\begin{figure}[h!]
|
||||
\centering
|
||||
\includegraphics[width=0.75\textwidth]{train_augmented.png}
|
||||
\caption{Sample images from the training dataset, showing the effect of data augmentation.}
|
||||
\end{figure}
|
||||
|
||||
\section{Feature Extraction} \label{sec:features}
|
||||
To train the simpler models, four different types of low-level features were extracted from the images:
|
||||
\begin{itemize}
|
||||
\item \textbf{Color Histogram (C):} Each channel's pixel intensities are quantized into 64 bins and counted, producing a normalized histogram. For RGB images this yields $3 \times 64 = 192$ features, while for grayscale images it yields 64 features. This descriptor captures the global color distribution of the image, regardless of spatial layout.
|
||||
|
||||
\item \textbf{Edge Direction Histogram (E):} Horizontal and vertical gradients are computed via Sobel filtering on the grayscale version of the image. The gradient angle at each pixel is quantized into 64 bins and accumulated using the gradient magnitude as weight, producing a normalized 64-dimensional descriptor. This captures the dominant edge orientations present in the image.
|
||||
|
||||
\item \textbf{RGB Co-occurrence Matrix (R):} Each channel is quantized into 3 levels and the channels are combined into a single code per pixel ($3^3 = 27$ possible values for RGB, $3$ for grayscale). Co-occurrence matrices are then computed along the horizontal and vertical directions at a distance of 10 pixels, symmetrized, and flattened into a normalized feature vector of $27^2 = 729$ features (or $3^2 = 9$ for grayscale). This descriptor captures local texture patterns by encoding spatial relationships between neighboring pixel values.
|
||||
|
||||
\item \textbf{Histogram of Oriented Gradients (HOG, H):} Computed using the \texttt{scikit-image} implementation with 9 orientation bins, $32 \times 32$ pixel cells, $2 \times 2$ cell blocks, and power-law (square root) compression. The image is divided into a grid of cells; within each cell, gradient orientations are binned and weighted by magnitude, then normalized across overlapping blocks. This produces a descriptor that effectively encodes local shape and edge structure, yielding 900 features for the $200 \times 200$ images.
|
||||
|
||||
\end{itemize}
|
||||
|
||||
All features were extracted once from the (augmented) training images and standardized to zero mean and unit variance, with the same transformation applied to the validation and test sets using the training statistics. The resulting feature vectors were then concatenated when multiple feature types were used together.
|
||||
|
||||
\section{Low-Level Features Models}
|
||||
This sections presents the different models used for classification along with their performance metrics.
|
||||
|
||||
\subsection{Logistic Regression}
|
||||
The first classifier is a multinomial logistic regression model. Given an input feature vector $\mathbf{x} \in \mathbb{R}^d$, the model computes class logits via an affine transformation:
|
||||
\begin{equation}
|
||||
\mathbf{z} = W\mathbf{x} + \mathbf{b}, \qquad W \in \mathbb{R}^{K \times d},\; \mathbf{b} \in \mathbb{R}^K,
|
||||
\end{equation}
|
||||
where $K = 20$ is the number of classes and $d$ is the dimensionality of the feature vector. The predicted probability for class $k$ is obtained via the softmax function:
|
||||
\begin{equation}
|
||||
P(y = k \mid \mathbf{x}) = \frac{\exp(z_k)}{\sum_{j=0}^{K-1} \exp(z_j)}.
|
||||
\end{equation}
|
||||
The model is trained by minimizing the cross-entropy loss over the training set:
|
||||
\begin{equation}
|
||||
\mathcal{L} = -\frac{1}{N}\sum_{i=0}^{N-1} \log P(y = y_i \mid \mathbf{x}_i),
|
||||
\end{equation}
|
||||
|
||||
using the Adam optimizer with a learning rate of $10^{-3}$. A maximum training of 50 epochs together with early stopping with a patience of 25 steps on the validation loss is employed to prevent overfitting. To determine which features are most informative, logistic regression was trained on all 15 possible combinations of the four feature types (C, E, R, H).
|
||||
|
||||
Example of training curves can be found in figure \ref{fig:train_curves_color_logistic}, where it's evident that convergence is largely achieved much earlier than the maximum number of epochs.
|
||||
|
||||
\begin{figure}[h!]
|
||||
\centering
|
||||
\begin{subfigure}{0.48\textwidth}
|
||||
\centering
|
||||
\includegraphics[width=\textwidth]{edge_dir_train.png}
|
||||
\caption{Edge Direction Histogram.}
|
||||
\end{subfigure}
|
||||
\hfill
|
||||
\begin{subfigure}{0.48\textwidth}
|
||||
\centering
|
||||
\includegraphics[width=\textwidth]{hog_train.png}
|
||||
\caption{Histogram of Oriented Gradients.}
|
||||
\end{subfigure}
|
||||
\caption{Logistic regression training curves for different low level features.}
|
||||
\label{fig:train_curves_color_logistic}
|
||||
\end{figure}
|
||||
|
||||
\begin{figure}[h!]
|
||||
\centering
|
||||
\includegraphics[width=0.9\textwidth]{logistic_color_summary.png}
|
||||
\caption{Summary of training (semi-transparent) and validation (solid) performance for different low-level feature combinations with logistic regression.}
|
||||
\label{fig:color_recap_logistic}
|
||||
\end{figure}
|
||||
|
||||
From figure \ref{fig:color_recap_logistic} it's evident that any feature combination containing HOG (H) performs significantly beter than any other combination. Also, a significant step can be noticed for the combinations containing the \emph{Edge Direction Histogram} (E). The reason behind the performance of the HOG descriptor is in it's superior ability to capture local shape and edge information, which is crucial for distinguishing between different road signs, as can be visually observed in figure \ref{fig:hogging} (the same reasoning, to a lesser extent, applies to the E descriptor).
|
||||
|
||||
\begin{figure}[h!]
|
||||
\centering
|
||||
\includegraphics[width=0.75\textwidth]{hogging.png}
|
||||
\caption{Visualization of the \emph{Histogram of Oriented Gradients} for a sample image. It's evident how HOG features perfectly capture shape and edge information, crucial for road sign classification.}
|
||||
\label{fig:hogging}
|
||||
\end{figure}
|
||||
|
||||
\subsection{Feature reduction}
|
||||
Having identified HOG as the most efficient feature type, a further step was to evaluate whether reducing the dimensionality of the HOG features could lead to a deterioration in performance. The feature reduction procedure was split into two steps:
|
||||
\begin{itemize}
|
||||
\item \textbf{removal of low-variance features}: only features with variances above a set percentile were retained; using the top 30\% variance features reduced the feature dimensionality from 900 to 270 while maintaining the same validation accuracy of 100\%.
|
||||
\item \textbf{Principal Component Analysis (PCA)}: PCA was applied to the HOG features to further reduce dimensionality while retaining 95\% of the variance. This resulted in a further reduction from 270 to 57 features, with a slight decrease in validation accuracy to 97\%.
|
||||
\end{itemize}
|
||||
|
||||
The final performance of the logistic regression model with the reduced HOG features was evaluated on the test set, achieving an accuracy of 97.5\%, confirming that the dimensionality reduction did not significantly impact the model's ability to generalize to unseen data.
|
||||
|
||||
\subsection{Grayscale}
|
||||
The Logistic Regression model was then trained on grayscale images, using properly extracted features (C, E, R, H). In figure \ref{fig:grayscale_recap_logistic} the same recap of training and validation performance can be found. As expected, HOG and Edge Direction Histogram (E) performances are almost unchanged, since they capture only shape and edge information, not depending on color. On the other hand, the performance of the color histogram (C) and RGB co-occurrence matrix (R) features significantly deteriorates, since they are not able to capture any useful information from grayscale images.
|
||||
|
||||
\begin{figure}[h!]
|
||||
\centering
|
||||
\includegraphics[width=0.9\textwidth]{logistic_gray_summary.png}
|
||||
\caption{Summary of training (semi-transparent) and validation (solid) performance for different low-level feature combinations with logistic regression on grayscale images.}
|
||||
\label{fig:grayscale_recap_logistic}
|
||||
\end{figure}
|
||||
|
||||
\subsection{Multi-Layer Perceptron}
|
||||
Given that logistic regression already achieved near-perfect accuracy with HOG features (a quick test with a two-hidden-layer MLP, 50 and 30 units, on the same reduced HOG features confirmed this, yielding comparable results) the more interesting question is whether an MLP can improve classification performance on the remaining feature types (C, E, R). By introducing hidden layers with ReLU activations, the MLP can learn non-linear decision boundaries that a single linear layer cannot capture, potentially extracting more discriminative information from features like color histograms and co-occurrence matrices.
|
||||
|
||||
Different MLPs have been trained on C, E, R feature combinations with same max epochs and patience as the logistic regression. Adam optimizer and cross entropy loss were chosen as well. The additional peculiarities of these architectures are:
|
||||
\begin{itemize}
|
||||
\item \textbf{Feature Reduction}: a more conservative approach was followed, retaining the top 50\% variance features without applying PCA. Unlike logistic regression, MLPs can learn to ignore irrelevant features through training, so aggressive dimensionality reduction is unnecessary and could discard useful patterns.
|
||||
\item \textbf{Hidden layer structure}: the number and width of hidden layers were determined automatically from the input dimensionality using a reduction factor of 3. Starting from the input size, each successive hidden layer is a third as wide as the previous one, and layers are added until the width falls below $2K= 40$ (twice the number of classes). This ensures a gradual bottleneck without excessive parameterization.
|
||||
\end{itemize}
|
||||
|
||||
\begin{figure}[h!]
|
||||
\centering
|
||||
\includegraphics[width=0.9\textwidth]{mlp_no_hog_summary.png}
|
||||
\caption{Comparison of performance (both training and validation) on color and grayscale images with different MLPs.}
|
||||
\label{fig:recap_mlp}
|
||||
\end{figure}
|
||||
|
||||
As is evident from figure \ref{fig:recap_mlp}, while some improvement can be noticed for the combination of \emph{Edge Direction Histogram} and \emph{RGB Co-occurrence Matrix}, the remaining combinations do not benefit significantly from the increased complexity. For grayscale images often the performance even deteriorates, likely due to the reduced amount of information contained in the features, not sufficient to train properly the larger number of parameters. A general tendency to overfit can be noticed across the board, especially for RGB images.
|
||||
|
||||
\section{Convolutional Neural Network}
|
||||
Finally, a simple Convolutional Neural Network (CNN) architecture was implemented and trained on the raw images to see how it would perform compared to simpler models with low-level features and especially HOG. The architecture, summarized in table \ref{tab:cnn_arch}, consists of three convolutional blocks followed by two fully connected layers. Each convolutional block includes a convolutional layer with ReLU activation, batch normalization, and max pooling for downsampling. The final fully connected layers reduce the feature dimensionality to the number of classes (20) for classification.
|
||||
|
||||
\begin{table}[h!]
|
||||
\centering
|
||||
\caption{CNN architecture. $C = 3$ for RGB, $C = 1$ for grayscale.}
|
||||
\label{tab:cnn_arch}
|
||||
\begin{tabular}{@{}l@{\hskip 1.5em}l@{\hskip 1.5em}l@{}}
|
||||
\toprule
|
||||
Block & Layers & Output Shape \\
|
||||
\midrule
|
||||
Input & --- & $C \times 200 \times 200$ \\
|
||||
Conv Block 1 & Conv2d($5 \times 5$, 16), BN, ReLU, MaxPool(2) & $16 \times 100 \times 100$ \\
|
||||
Conv Block 2 & Conv2d($3 \times 3$, 32), BN, ReLU, MaxPool(2) & $32 \times 50 \times 50$ \\
|
||||
Conv Block 3 & Conv2d($3 \times 3$, 64), BN, ReLU, MaxPool(2) & $64 \times 25 \times 25$ \\
|
||||
Flatten & Flatten & $40{,}000$ \\
|
||||
FC Layer 1 & Linear(256), ReLU, Dropout(0.5) & $256$ \\
|
||||
FC Layer 2 & Linear($K$) & $K = 20$ \\
|
||||
\bottomrule
|
||||
\end{tabular}
|
||||
\end{table}
|
||||
|
||||
The training was performed using the Adam optimizer with an initial learning rate of $10^{-3}$, a batch size of 32, and the same early stopping criteria as the previous models, with an increased patience (200 steps). A scheduler was added to reduce the learning rate when no improvement was observed for 50 steps, down to $10^{-6}$. Data augmentation was applied on the fly during training to enhance generalization as explained in section \ref{sec:augmentation}.
|
||||
|
||||
As expected, training converged more slowly than the previous models due to the increased complexity and number of parameters (figure \ref{fig:cnn_training}). However, the CNN achieved a validation accuracy of 99\% and a test accuracy of 100\%, outperforming all previous models, including those using HOG features. Similar results were obtained when training the same architecture on grayscale images, confirming the CNN's ability to learn robust features directly from the raw pixel data.
|
||||
|
||||
\begin{figure}[h!]
|
||||
\centering
|
||||
\includegraphics[width=0.8\textwidth]{cnn_train_color.png}
|
||||
\caption{CNN training curves for RGB images.}
|
||||
\label{fig:cnn_training}
|
||||
\end{figure}
|
||||
|
||||
\subsection{Activation Maps}
|
||||
An interesting observation can be made by comparing grayscale and RGB activation maps of the first convolutional layer (figure \ref{fig:activation_maps}). The RGB activation maps show a stronger focus on color-specific regions, while the grayscale maps rely more heavily on contrast and shape information. This highlights how the CNN adapts its feature extraction process based on the input data, effectively learning to utilize the most relevant information for classification.
|
||||
|
||||
\begin{figure}[h!]
|
||||
\centering
|
||||
\includegraphics[width=\textwidth]{cnn_activation_maps.png}
|
||||
\caption{Comparison of first-layer activation maps for RGB and grayscale inputs. The RGB maps show stronger responses to color features, while the grayscale maps focus more on edges, shapes and contrast.}
|
||||
\label{fig:activation_maps}
|
||||
\end{figure}
|
||||
|
||||
\section{Conclusion}
|
||||
This report explored road sign classification using models of increasing complexity, from logistic regression on hand-crafted features to a convolutional neural network operating on raw pixels. The results highlight two key findings. First, among low-level features, HOG proved overwhelmingly dominant: its ability to encode local shape and edge structure allowed even a simple linear classifier to reach near-perfect accuracy, while color- and texture-based descriptors (C, R) provided limited discriminative power on their own. Introducing non-linear models (MLPs) on the non-HOG features yielded only marginal improvements and often led to overfitting, suggesting that the bottleneck lies in the features themselves rather than in model capacity. Second, the CNN achieved the best overall performance (100\% test accuracy) while requiring no manual feature engineering, confirming that end-to-end learning can surpass carefully designed pipelines when sufficient model capacity and regularization are provided. A comparison between RGB and grayscale inputs further revealed that color information, while beneficial for hand-crafted descriptors like C and R, is largely redundant for shape-aware methods (HOG, E) and for the CNN, which learns to compensate through its convolutional filters.
|
||||
|
||||
|
||||
|
||||
|
||||
\end{document}
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 872 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 71 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 87 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 30 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 117 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 60 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 58 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 53 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 686 KiB |
Loading…
Reference in New Issue