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CNN Intro

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Martin Thoma 2019-02-10 22:31:43 +01:00
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presentations/CNN-Intro/CNN-Intro.tex
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@ -4,6 +4,7 @@
\usepackage[utf8]{inputenc} % this is needed for german umlauts
\usepackage[english]{babel} % this is needed for german umlauts
\usepackage[T1]{fontenc} % this is needed for correct output of umlauts in pdf
\usepackage{caption}
\usepackage{tikz}
\usetikzlibrary{arrows.meta}
\usetikzlibrary{decorations.pathreplacing}
@ -11,6 +12,7 @@
\usetikzlibrary{decorations.text}
\usetikzlibrary{decorations.pathmorphing}
\usetikzlibrary{shapes.multipart, calc}
\usepackage{minted} % needed for the inclusion of source code
\begin{document}
@ -107,13 +109,94 @@
\section{Applications}
\begin{frame}{Symbol recognizer}
\begin{center}
\href{http://write-math.com}{write-math.com}
\end{center}
\begin{figure}[ht]
\centering
\includegraphics[width=0.8\paperwidth, height=0.7\paperheight, keepaspectratio]{graphics/symbol-recognizer.png}
\captionsetup{labelformat=empty}
\caption{\href{http://write-math.com}{write-math.com}}
\end{figure}
\end{frame}
\begin{frame}{Symbol recognizer}
GANs
\begin{frame}{}
\inputminted[linenos,
numbersep=7pt,
gobble=0,
% frame=none,
% framesep=2mm,
fontsize=\footnotesize, tabsize=4]{python}{cnn.py}
\end{frame}
\begin{frame}{Super Resolution}
\begin{figure}[ht]
\centering
\includegraphics[width=0.8\paperwidth, height=0.7\paperheight, keepaspectratio]{graphics/pixel-recursive-super-resolution.png}
\captionsetup{labelformat=empty}
\caption{Dahl, Norouzi, Shlens: Pixel recursive super resolution (2017)}
\end{figure}
\end{frame}
\begin{frame}{Colorization: The Problem}
\begin{figure}[ht]
\centering
\includegraphics[width=0.8\paperwidth, height=0.7\paperheight, keepaspectratio]{graphics/multimodality-apple.png}
\captionsetup{labelformat=empty}
\caption{Cinarel: Automatic Colorization of Webtoons Using Deep Convolutional Neural Networks (2018)}
\end{figure}
Interactive Demo: \href{http://richzhang.github.io/colorization/}{richzhang.github.io/colorization}
\end{frame}
\begin{frame}{Colorization - Photographs}
\begin{figure}[ht]
\centering
\includegraphics[width=0.8\paperwidth, height=0.7\paperheight, keepaspectratio]{graphics/colorful-image-colorization.png}
\captionsetup{labelformat=empty}
\caption{Zhang, Isola, Efros: Colorful Image Colorization (2016)}
\end{figure}
Interactive Demo: \href{http://richzhang.github.io/colorization/}{richzhang.github.io/colorization}
\end{frame}
\begin{frame}{Colorization - Comic}
\begin{figure}[ht]
\centering
\includegraphics[width=0.8\paperwidth, height=0.7\paperheight, keepaspectratio]{graphics/comic-colorization.png}
\captionsetup{labelformat=empty}
\caption{Ci, Ma, Wang, Li, Luo: User-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks (2018)}
\end{figure}
\end{frame}
\begin{frame}{Denoising}
\begin{figure}[ht]
\centering
\includegraphics[width=0.8\paperwidth, height=0.7\paperheight, keepaspectratio]{graphics/denoising.png}
\captionsetup{labelformat=empty}
\caption{Zhang, Zuo, Gu, Zhang: Learning Deep CNN Denoiser Prior for Image Restoration (2017)}
\end{figure}
\end{frame}
\begin{frame}{Image Inpainting (Watermark removal)}
\begin{figure}[ht]
\centering
\includegraphics[width=0.8\paperwidth, height=0.7\paperheight, keepaspectratio]{graphics/leopard-inpainting.png}
\captionsetup{labelformat=empty}
\caption{Yang, Lu, Lin, Shechtman, Wang, Li: High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis (2017)}
\end{figure}
\end{frame}
\begin{frame}{CNNs in NLP}
\begin{figure}[ht]
\centering
\includegraphics[width=0.8\paperwidth, height=0.7\paperheight, keepaspectratio]{graphics/tdnns.png}
\captionsetup{labelformat=empty}
\caption{Collobert, Weston, Bottou, Karlen, Kavukcuoglu, Kuksa:
Natural Language Processing (almost) from Scratch (2011)}
\end{figure}
\end{frame}
\end{document}