# HG changeset patch
# User Xavier Glorot <glorotxa@iro.umontreal.ca>
# Date 1275260076 14400
# Node ID 6593e67381a302a9dffe5fb1112f5c071601e43d
# Parent  5a1a264aaad68a7d17d10b2331906356063cc1ee
Added transformation figure

diff -r 5a1a264aaad6 -r 6593e67381a3 writeup/images/transfo.png
Binary file writeup/images/transfo.png has changed
diff -r 5a1a264aaad6 -r 6593e67381a3 writeup/nips2010_submission.tex
--- a/writeup/nips2010_submission.tex	Sun May 30 17:49:14 2010 -0400
+++ b/writeup/nips2010_submission.tex	Sun May 30 18:54:36 2010 -0400
@@ -277,6 +277,19 @@
 \end{figure}
 
 
+\begin{figure}[h]
+\resizebox{.99\textwidth}{!}{\includegraphics{images/transfo.png}}\\
+\caption{Illustration of each transformation applied to the same image
+of the upper-case h (upper-left image). first row (from left to rigth) : original image, slant,
+thickness, affine transformation, local elastic deformation; second row (from left to rigth) :
+pinch, motion blur, occlusion, pixel permutation, gaussian noise; third row (from left to rigth) :
+background image, salt and pepper noise, spatially gaussian noise, scratches,
+color and contrast changes.}
+\label{fig:transfo}
+\end{figure}
+
+
+
 \section{Experimental Setup}
 
 Whereas much previous work on deep learning algorithms had been performed on
@@ -302,7 +315,7 @@
 The fourth series, $hsf_4$, experimentally recognized to be the most difficult one is recommended 
 by NIST as testing set and is used in our work and some previous work~\cite{Granger+al-2007,Cortes+al-2000,Oliveira+al-2002,Milgram+al-2005}
 for that purpose. We randomly split the remainder into a training set and a validation set for
-model selection. The sizes of these data sets are: XXX for training, XXX for validation, 
+model selection. The sizes of these data sets are:  for training, XXX for validation, 
 and XXX for testing.
 The performances reported by previous work on that dataset mostly use only the digits.
 Here we use all the classes both in the training and testing phase. This is especially
@@ -312,7 +325,14 @@
 of letters in the test set, not in the training set (more like the natural distribution
 of letters in text).
 
-\item {\bf Fonts} TODO!!!
+\item {\bf Fonts} 
+In order to have a good variety of sources we downloaded an important number of free fonts from: {\tt http://anonymous.url.net}
+%real adress {\tt http://cg.scs.carleton.ca/~luc/freefonts.html}
+in addition to Windows 7's, this adds up to a total of $9817$ different fonts that we can choose uniformly.
+The ttf file is either used as input of the Captcha generator (see next item) or, by producing a corresponding image, 
+directly as input to our models.
+
+
 
 \item {\bf Captchas}
 The Captcha data source is an adaptation of the \emph{pycaptcha} library (a python based captcha generator library) for 
diff -r 5a1a264aaad6 -r 6593e67381a3 writeup/techreport.tex
--- a/writeup/techreport.tex	Sun May 30 17:49:14 2010 -0400
+++ b/writeup/techreport.tex	Sun May 30 18:54:36 2010 -0400
@@ -410,6 +410,18 @@
 \end{figure}
 
 
+\begin{figure}[h]
+\resizebox{.99\textwidth}{!}{\includegraphics{images/transfo.png}}\\
+\caption{Illustration of each transformation applied to the same image
+of the upper-case h (upper-left image). first row (from left to rigth) : original image, slant,
+thickness, affine transformation, local elastic deformation; second row (from left to rigth) :
+pinch, motion blur, occlusion, pixel permutation, gaussian noise; third row (from left to rigth) :
+background image, salt and pepper noise, spatially gaussian noise, scratches,
+color and contrast changes.}
+\label{fig:transfo}
+\end{figure}
+
+
 \section{Experimental Setup}
 
 \subsection{Training Datasets}