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For more info see http://www.lyx.org/ \lyxformat 544 \begin_document \begin_header \save_transient_properties true \origin unavailable \textclass article \begin_preamble \def\changemargin#1#2{\list{}{\rightmargin#2\leftmargin#1}\item[]} \let\endchangemargin=\endlist \pagenumbering{roman} \usepackage{color} \definecolor{commentgreen}{RGB}{0,94,11} \end_preamble \use_default_options true \begin_modules customHeadersFooters minimalistic todonotes \end_modules \maintain_unincluded_children false \language british \language_package default \inputencoding auto \fontencoding global \font_roman "default" "default" \font_sans "default" "default" \font_typewriter "default" "default" \font_math "auto" "auto" \font_default_family default \use_non_tex_fonts false \font_sc false \font_osf false \font_sf_scale 100 100 \font_tt_scale 100 100 \use_microtype true \use_dash_ligatures true \graphics default \default_output_format default \output_sync 0 \bibtex_command biber \index_command default \paperfontsize 11 \spacing onehalf \use_hyperref true \pdf_title "Convolutional Neural Networks with DIGITS" \pdf_author "Andy Pack" \pdf_subject "EEEM063 Image Processing & Deep Learning" \pdf_keywords "EEEM063" \pdf_bookmarks true \pdf_bookmarksnumbered false \pdf_bookmarksopen false \pdf_bookmarksopenlevel 1 \pdf_breaklinks false \pdf_pdfborder true \pdf_colorlinks false \pdf_backref false \pdf_pdfusetitle true \papersize default \use_geometry true \use_package amsmath 1 \use_package amssymb 1 \use_package cancel 1 \use_package esint 1 \use_package mathdots 1 \use_package mathtools 1 \use_package mhchem 1 \use_package stackrel 1 \use_package stmaryrd 1 \use_package undertilde 1 \cite_engine biblatex \cite_engine_type authoryear \biblio_style plain \biblio_options urldate=long \biblatex_bibstyle ieee \biblatex_citestyle ieee \use_bibtopic false \use_indices false \paperorientation portrait \suppress_date true \justification true \use_refstyle 1 \use_minted 0 \index Index \shortcut idx \color #008000 \end_index \leftmargin 2cm \topmargin 2cm \rightmargin 2cm \bottommargin 2cm \secnumdepth 3 \tocdepth 3 \paragraph_separation skip \defskip medskip \is_math_indent 0 \math_numbering_side default \quotes_style british \dynamic_quotes 0 \papercolumns 1 \papersides 1 \paperpagestyle fancy \bullet 1 0 9 -1 \bullet 2 0 24 -1 \tracking_changes false \output_changes false \html_math_output 0 \html_css_as_file 0 \html_be_strict false \end_header \begin_body \begin_layout Title \size giant Convolutional Neural Networks with DIGITS \end_layout \begin_layout Author Andy Pack \end_layout \begin_layout Standard \begin_inset VSpace 15pheight% \end_inset \end_layout \begin_layout Standard \align center \begin_inset Graphics filename surrey.png lyxscale 15 width 40col% \end_inset \end_layout \begin_layout Standard \begin_inset VSpace vfill \end_inset \end_layout \begin_layout Standard \noindent \align center EEEM063 \begin_inset Newline newline \end_inset May 2021 \size large \begin_inset Newline newline \end_inset Department of Electrical and Electronic Engineering \begin_inset Newline newline \end_inset Faculty of Engineering and Physical Sciences \begin_inset Newline newline \end_inset University of Surrey \end_layout \begin_layout Standard \begin_inset Newpage newpage \end_inset \end_layout \begin_layout Abstract abstract \end_layout \begin_layout Standard \begin_inset CommandInset toc LatexCommand tableofcontents \end_inset \end_layout \begin_layout List of TODOs \end_layout \begin_layout Standard \begin_inset Newpage newpage \end_inset \end_layout \begin_layout Standard \begin_inset FloatList figure \end_inset \end_layout \begin_layout Standard \begin_inset FloatList table \end_inset \end_layout \begin_layout Standard \begin_inset CommandInset toc LatexCommand lstlistoflistings \end_inset \end_layout \begin_layout Standard \begin_inset Newpage newpage \end_inset \end_layout \begin_layout Right Footer Andy Pack / 6420013 \end_layout \begin_layout Left Footer May 2021 \end_layout \begin_layout Left Header EEEM063 Coursework \end_layout \begin_layout Standard \begin_inset ERT status open \begin_layout Plain Layout \backslash pagenumbering{arabic} \end_layout \begin_layout Plain Layout \backslash setcounter{page}{1} \end_layout \end_inset \end_layout \begin_layout Section Introduction \end_layout \begin_layout Standard Although much of the theory for convolutional neural networks (CNNs) was developed throughout the 20th century, their importance to the field of computer vision was not widely appreciated until the early 2010s. \begin_inset Flex TODO Note (inline) status open \begin_layout Plain Layout More context \end_layout \end_inset \end_layout \begin_layout Standard Although CNNs can appear opaque when attempting to understand how decisions are made, they are not black boxes and there are many ways to affect a model's performance. This work presents investigations into how a CNN's performance is affected by the subject dataset, the architecture of the network and the parameters used when training. Section \begin_inset CommandInset ref LatexCommand ref reference "sec:Investigations-Scope" plural "false" caps "false" noprefix "false" \end_inset outlines the scope of the investigations made herein, describing the motivation for the variations and expectations as to how this would affect performance. The results for these investigations are presented in section \begin_inset CommandInset ref LatexCommand ref reference "sec:Results" plural "false" caps "false" noprefix "false" \end_inset with interpretations made in the following section. Section \begin_inset CommandInset ref LatexCommand ref reference "sec:Conclusions" plural "false" caps "false" noprefix "false" \end_inset summarises and concludes the work. \end_layout \begin_layout Section Investigations Scope \begin_inset CommandInset label LatexCommand label name "sec:Investigations-Scope" \end_inset \end_layout \begin_layout Standard \begin_inset Flex TODO Note (inline) status open \begin_layout Plain Layout Dataset \end_layout \end_inset \end_layout \begin_layout Subsection Dataset Processing \end_layout \begin_layout Standard \begin_inset Flex TODO Note (inline) status open \begin_layout Plain Layout Mean shift/whitening/augmentation \end_layout \end_inset \end_layout \begin_layout Subsection Meta-Parameters \end_layout \begin_layout Standard \begin_inset Flex TODO Note (inline) status open \begin_layout Plain Layout Epochs/learning rate/momentum? \end_layout \end_inset \end_layout \begin_layout Subsection Network Architectures \end_layout \begin_layout Subsubsection Convolutional Layers \end_layout \begin_layout Subsubsection Fully-Connected Layers \end_layout \begin_layout Standard Following the convolutional stages there are three dense or fully-connected layers which provide two key features in image classification. The first is flattening the 2D cross-section of the preceding convolutional layers into a 1D representation for propagation to a final one-hot vector output. The second is as a traditional multi-layer perceptron classifier, taking the high-level visual insights of the later convolutional layers and reasoning these into a final classification. When treated as an MLP, these can instead be considered as 2 hidden layers and a single output layer. The reason for designating the last layer separately is the level to which it is fixed when varying the classifier as a whole. The number of neurons in this layer remains equal to the number of classes in the dataset in order to form a one-hot vector output when the network makes a classification. \end_layout \begin_layout Subsubsection Non-Linearity \end_layout \begin_layout Standard The inclusion of non-linear layers throughout AlexNet is critical to it's ability to learn complex insights into a dataset. Convolution as a mathematical operation can be proven to be associative \begin_inset Flex TODO Note (Margin) status open \begin_layout Plain Layout Fubini's theorem \end_layout \end_inset in a similar fashion to multiplication. This means that consecutive convolutions can be collapsed into a single operation, for example multiple filters can be merged into a single compound operation for less expensive application to an image. \end_layout \begin_layout Section Results \begin_inset CommandInset label LatexCommand label name "sec:Results" \end_inset \end_layout \begin_layout Section Discussion \begin_inset CommandInset label LatexCommand label name "sec:Discussion" \end_inset \end_layout \begin_layout Section Conclusions \begin_inset CommandInset label LatexCommand label name "sec:Conclusions" \end_inset \end_layout \begin_layout Standard \begin_inset Newpage newpage \end_inset \end_layout \begin_layout Standard \begin_inset CommandInset label LatexCommand label name "sec:bibliography" \end_inset \begin_inset CommandInset bibtex LatexCommand bibtex btprint "btPrintCited" bibfiles "references" options "bibtotoc" \end_inset \begin_inset Newpage pagebreak \end_inset \end_layout \begin_layout Section \start_of_appendix Source Code \begin_inset CommandInset label LatexCommand label name "sec:Code" \end_inset \end_layout \end_body \end_document