-
Notifications
You must be signed in to change notification settings - Fork 1
afrozalm/LeNet
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
\documentclass{article} \usepackage{graphicx} \usepackage{verbatim} \author{Mohammad Afroz Alam} \date{} \title{CV Assignment 3 Readme} \begin{document} \section{Time Taken} \begin{itemize} \item Time taken for conv1 = 0.000958919525146 secs \item Time taken for conv2 = 0.00978302955627 secs \item Time taken for conv3 = 0.00294518470764 secs \item Time taken for conv4 = 0.00292491912842 secs \item Time taken for conv5 = 0.0381109714508 secs \item Time taken for fc1 = 0.000120878219604 secs \item Time taken for fc2 = 0.000124216079712 secs \end{itemize} \section{Number of Parameters} \begin{itemize} \item Conv 1 : 155 \item Conv 2 : 2416 \item Fc 1 : 48120 \item Fc 2 : 10164 \item Fc 3 : 850 \end{itemize} \section{t-SNE plots} \begin{figure}[h] \centering \includegraphics[width=0.7\textwidth]{keras_lenet/scatter_basic.png} \caption{Without 84 dimensional features for 50000 images} \label{fig:basic} \end{figure} \begin{figure}[h] \centering \includegraphics[width=0.7\textwidth]{keras_lenet/scatter_encoding.png} \caption{With 84 dimensional features for 10000 images(Keras)} \end{figure} \begin{figure}[h] \centering \includegraphics[width=0.7\textwidth]{scatter_encoding.png} \caption{With 84 dimensional features for 10000 images (My Implementation)} \end{figure} \section{Training and Validation Losses} \begin{figure}[h] \centering \includegraphics[width=0.7\textwidth]{loss.png} \caption{Train and Validation loss for batch size 160 (My Implementation)} \end{figure} \begin{figure}[h] \centering \includegraphics[width=0.7\textwidth]{accuracy.png} \caption{Train and Validation accuracy for batch size 160 (My Implementation)} \end{figure} \begin{figure}[h] \centering \includegraphics[width=\textwidth]{keras_lenet/acc_epoch.png} \caption{Accuracy on different batch sizes per epoch (Keras)} \end{figure} \begin{figure}[h] \centering \includegraphics[width=\textwidth]{keras_lenet/acc_time.png} \caption{Accuracy on different batch sizes per time (Keras)} \end{figure} \begin{figure}[h] \centering \includegraphics[width=\textwidth]{keras_lenet/loss_epoch.png} \caption{Loss on different batch sizes per epoch (Keras)} \end{figure} \begin{figure}[h] \centering \includegraphics[width=\textwidth]{keras_lenet/loss_time.png} \caption{Loss on different batch sizes per epoch (Keras)} \end{figure} \subsection{Conclusion} The training converges fastest with batch size 64 when we observe the loss and accuracy with respect to time. \end{document} %%% Local Variables: %%% mode: latex %%% TeX-master: t %%% End:
About
Implemented LeNel-5 from scratch using numpy and scipy
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published