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\setlength{\headheight}{13.6pt}
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\setlength{\headheight}{13.6pt}
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% numeric
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% numeric
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\usepackage[style=ieee,sorting=none,backend=biber]{biblatex}
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\usepackage[bibstyle=ieee, citestyle=numeric, sorting=none,backend=biber]{biblatex}
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\addbibresource{../main.bib}
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\addbibresource{../main.bib}
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% Write the approved title of your dissertation
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% Write the approved title of your dissertation
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This method is more effective at allowing users to add new types of products but as it does not give defined classes as the output the system does not give the target functionality that this project is hoping to achive.
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This method is more effective at allowing users to add new types of products but as it does not give defined classes as the output the system does not give the target functionality that this project is hoping to achive.
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\subsection{Alternatives to my Project}
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There currently exist systems that do image classification, like Google Vision AI \cite{google-vision-api}, and Amazon's Rekoginition \cite{amazon-rekognition}.
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Their tools, while providing similar services to what my project is supposed to do, it mostly focusses on general image classification rather than specific image classification, i.e. Car vs Boat, vs, Car model X vs Car model Y.
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\subsection{Creation Models}
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\subsection{Creation Models}
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The models that I will be creating will be Convolutional Neural Network(CNN) \cite{lecun1989handwritten,fukushima1980neocognitron}.
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The models that I will be creating will be Convolutional Neural Network(CNN) \cite{lecun1989handwritten,fukushima1980neocognitron}.
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The system will be creating two types of models that cannot be expanded and models that can be expanded. For the models that can be expanded, see the section about expandable models.
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The system will be creating two types of models that cannot be expanded and models that can be expanded. For the models that can be expanded, see the section about expandable models.
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