tex-projects/LaTeX-examples
2
0
Fork 0
mirror of https://github.com/MartinThoma/LaTeX-examples.git synced 2025-04-19 11:38:05 +02:00
Code Activity

restructured presentation

Browse source
This commit is contained in:
Martin Thoma 2014-08-20 17:55:30 -04:00
parent 75bc9d0dae
commit 3a8564348e
9 changed files with 103 additions and 58 deletions
Download patch file Download diff file Expand all files Collapse all files

13
presentations/Bachelor-Short/LaTeX/bachelor-short.tex
View file

@ -26,13 +26,20 @@
\section{What is my Bachelor's thesis about?}
\input{introduction}
\section{What did I do so far?}
\input{work-done}
\section{write-math.com}
\input{write-math}
\section{Preprocessing and Features}
\input{preprocessing}
\input{features}
\section{Neural Nets}
\input{neural-nets}
\section{What will I do next?}
\input{will-do}
\section{End}
\section*{End}
\subsection{End}
\input{sources}
\framedgraphic{Thanks for Your Attention!}{../images/xi.png}

23
presentations/Bachelor-Short/LaTeX/features.tex Normal file
View file

@ -0,0 +1,23 @@
\subsection{Features}
\begin{frame}{Features}
\begin{itemize}
\item Local
\begin{itemize}
\item Coordinates
\item Speed
\item Binary pen pressure
\item Direction
\item Curvature
\item Bitmap-environment
\item Hat-Feature
\end{itemize}
\item Global
\begin{itemize}
\item \# of points
\item \# of strokes
\item Center point
\item Bitmap
\item Bounding box (width, height, time)
\end{itemize}
\end{itemize}
\end{frame}

18
presentations/Bachelor-Short/LaTeX/introduction.tex
View file

@ -2,9 +2,9 @@
\begin{frame}{What is my Bachelor's thesis about?}
\begin{itemize}
\item Recognition of handwritten mathematical formulas
\item Recognition of handwritten mathematical symbols
\item On-line recognition, not OCR!
\item Given a series of points $(x(t), y(t), b)$\\
\item Given a series of points $(x(t), y(t), b(t))$\\
I want to get the proper \LaTeX{} code.
\end{itemize}
\end{frame}
@ -16,13 +16,13 @@
\item It's much harder to find complete formulas.
\end{itemize}
I want to
\begin{itemize}
\item provide a tool that enables beginners to get the best \LaTeX{} code
for their formula,
\item find out what works best for symbol recognition
\item and provide data and a platform to test new ideas for classifiers
\end{itemize}
% I want to
% \begin{itemize}
% \item provide a tool that enables beginners to get the best \LaTeX{} code
% for their formula,
% \item find out what works best for symbol recognition
% \item and provide data and a platform to test new ideas for classifiers
% \end{itemize}
As soon as symbol recognition works good in terms of classification time and
performance, I will continue with formula recognition.

13
presentations/Bachelor-Short/LaTeX/neural-nets.tex Normal file
View file

@ -0,0 +1,13 @@
\subsection{Neural Net experiments}
\begin{frame}{Experiments}
\textbf{Preprocessing:} Scaling, shifting and linear interpolation\\
\textbf{Features:} Coordinates of 80 points (4 Lines with 20 points each)\\
\textbf{Learning:} MLP, 300 epochs, LR of 0.1
\begin{itemize}
\item[] \textit{toplogy \tabto{6cm} error in training time}
\item 160:500:369 \tabto{6cm} 30.62 \% in \hphantom{0}9min 08s
\item 160:500:500:369 \tabto{6cm} 27.73 \% in 11min 49s
\item 160:500:500:500:369 \tabto{6cm} 34.79 \% in 14min 09s
\item 160:500:500:500:500:369 \tabto{6cm} 33.61 \% in 14min 06s
\end{itemize}
\end{frame}

18
presentations/Bachelor-Short/LaTeX/preprocessing.tex Normal file
View file

@ -0,0 +1,18 @@
\subsection{Preprocessing}
\begin{frame}{Preprocessing}
\begin{itemize}
\item Normalizing
\begin{itemize}
\item Scaling
\item Shifting
\item Resampling
\end{itemize}
\item Noise reduction
\begin{itemize}
\item Smoothing (e.g. moving average)
\item Dot reduction
\item Filtering (by distance, speed or angle)
\item Stroke connection
\end{itemize}
\end{itemize}
\end{frame}

42
presentations/Bachelor-Short/LaTeX/will-do.tex
View file

@ -1,32 +1,22 @@
\subsection{What will I do next?}
\begin{frame}{What will I do next?}
\begin{itemize}
\item Get classification performance with cross-validation
\item Implement neural net for classification
\begin{itemize}
\item preprocessing: compute cubic spline for each line
\begin{itemize}
\item equi-spaced points or
\item get equi-timed points
\end{itemize}
\item 5 - 20 input neurons for each line
\item 1076 output neurons (one for each symbol)
\end{itemize}
\item Get a language model (e.g. by parsing Wikipedia)
\item Use ANN with HMM (?)
\item Evaluate preprocessing steps
\item Try other features
\item Try other topologies / trainings (e.g. newbob)
\end{itemize}
\end{frame}
\subsection{Far future}
\begin{frame}{What could be done?}
\begin{itemize}
\item Make use of audio data in a multimodal approach\\
e.g. $R$ and $\mathcal{R}$
\item Currently, the Lecture Translation system doesn't recognize math.\\
You get \enquote{integral of e raised to the power of x d x} instead
of $\int e^x \mathrm{d} x$.
\item Spoken math is ambigous: $\sqrt{a+b}$ vs. $\sqrt{a} + b$
\item The language model I create could help to find probable formulas
\item The platform could be used to get more input data of users
\end{itemize}
\end{frame}
% \subsection{Far future}
% \begin{frame}{What could be done?}
% \begin{itemize}
% \item Make use of audio data in a multimodal approach\\
% e.g. $R$ and $\mathcal{R}$
% \item Currently, the Lecture Translation system doesn't recognize math.\\
% You get \enquote{integral of e raised to the power of x d x} instead
% of $\int e^x \mathrm{d} x$.
% \item Spoken math is ambigous: $\sqrt{a+b}$ vs. $\sqrt{a} + b$
% \item The language model I create could help to find probable formulas
% \item The platform could be used to get more input data of users
% \end{itemize}
% \end{frame}

32
presentations/Bachelor-Short/LaTeX/work-done.tex → presentations/Bachelor-Short/LaTeX/write-math.tex
View file

@ -13,25 +13,18 @@
\framedgraphic{Classify}{../images/classify.png}
\framedgraphic{Workflow}{../images/workflow.png}
\framedgraphic{User page}{../images/user-page.png}
\framedgraphic{Information about handwritten-data}{../images/view.png}
\framedgraphic{Non-mathematical symbols}{../images/yinyang.png}
\framedgraphic{Training}{../images/train.png}
% \framedgraphic{User page}{../images/user-page.png}
% \framedgraphic{Information about recordings}{../images/view.png}
% \framedgraphic{Symbol page}{../images/symbol.png}
% \framedgraphic{Training}{../images/train.png}
\framedgraphic{Ranking}{../images/ranking.png}
\framedgraphic{Symbol page}{../images/symbol.png}
\begin{frame}{Statistics}
\begin{frame}[fragile]{Statistics}
\begin{itemize}
\item 40 users
\item 1076 symbols
\item 5519 handwritten symbols (e.g. 195 times the letter \enquote{A})
\begin{itemize}
\item only 264 have 4 lines
\item only 36 have 5 lines
\item only 16 have 6 lines
\item only 19 have 7 lines or more
\item none has more than 12 lines
\end{itemize}
\item 127 users with at least 5 recordings
\item 1109 symbols, but only 369 used for experiments
\item $\num{235831}$ recordings (e.g. $\num{3486}$ times \verb+\int+)
\end{itemize}
\end{frame}
@ -40,12 +33,11 @@
\item preprocessing: Scale to fit into unit square while keeping the aspect
ratio
\item applies dynamic time warping
\item compares a new handwritten symbol with every handwritten symbol
\item compares a new recording with every recording
in the database
\item[$\Rightarrow$] Classification time is in $\mathcal{O}(\text{handwritten symbols})$,
\item[$\Rightarrow$] Classification time is in $\mathcal{O}(\text{recordings})$,
but we rather would like $\mathcal{O}(\text{symbols})$
\item the current server / workflow can only handle about 4000 handwritten
symbols
\item the current server / workflow can only handle about 4000 recordings
\item[$\Rightarrow$] Another way to classify is necessary
\end{itemize}
\end{frame}

BIN
presentations/Bachelor-Short/images/ranking.png
View file

Binary file not shown.
Side by side Swipe Overlay

Before

Width:  |  Height:  |  Size: 36 KiB

After

Width:  |  Height:  |  Size: 38 KiB

Before After
Before After

2
presentations/Bachelor-Short/templates/myStyle.sty
View file

@ -4,9 +4,11 @@
\InputIfFileExists{../templates/beamerthemekit.sty}{\usepackage{../templates/beamerthemekit}}{\usetheme{Frankfurt}}
\usefonttheme{professionalfonts}
\usepackage{tabto}
\usepackage{hyperref}
\usepackage{lmodern}
\usepackage{listings}
\usepackage{siunitx}
\usepackage{wrapfig} % see http://en.wikibooks.org/wiki/LaTeX/Floats,_Figures_and_Captions
\usepackage[utf8]{inputenc} % this is needed for german umlauts
\usepackage[english]{babel} % this is needed for german umlauts