296 lines
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296 lines
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<meta name="description" content="Starting to write a CNN # This week I started to implement what I had learnt about CNNs in Week 4. At this point I hadn’t designed a CNN architecture to implement, instead I wanted to have a running model regardless of performance just to see if I could implement one and understand it.
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Half way through implementation, I decided to look back at the existing research papers on judging aesthetic judgement to see which aspects of their system and CNN were important to the task.">
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<meta property="og:description" content="Starting to write a CNN # This week I started to implement what I had learnt about CNNs in Week 4. At this point I hadn’t designed a CNN architecture to implement, instead I wanted to have a running model regardless of performance just to see if I could implement one and understand it.
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Half way through implementation, I decided to look back at the existing research papers on judging aesthetic judgement to see which aspects of their system and CNN were important to the task." />
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<title>Week 5 | MMP | Oscar Pocock</title>
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<li><a href="#starting-to-write-a-cnn">Starting to write a CNN</a></li>
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<h1>
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<a href="/posts/week-5/">Week 5</a>
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</h1>
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<h5>March 6, 2022</h5>
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<h1 id="starting-to-write-a-cnn">
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Starting to write a CNN
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<a class="anchor" href="#starting-to-write-a-cnn">#</a>
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</h1>
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<p>This week I started to implement what I had learnt about CNNs in
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<a href="../week-4/">Week 4</a>. At this point I hadn’t designed a CNN architecture to implement, instead I wanted to have a running model regardless of performance just to see if I could implement one and understand it.</p>
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<p>Half way through implementation, I decided to look back at the existing research papers on judging aesthetic judgement to see which aspects of their system and CNN were important to the task. While reading I saw that nearly all research papers on the topic used transfer learning instead of creating their own CNNs from scratch. At this point I stopped writing a CNN from scratch and decided to solve my problem using transfer learning instead. I followed a guide<sup id="fnref:1"><a href="#fn:1" class="footnote-ref" role="doc-noteref">1</a></sup> on implementing transfer learning in pytorch and another guide<sup id="fnref:2"><a href="#fn:2" class="footnote-ref" role="doc-noteref">2</a></sup><sup id="fnref:3"><a href="#fn:3" class="footnote-ref" role="doc-noteref">3</a></sup> on creating a regressive CNN model.</p>
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<section class="footnotes" role="doc-endnotes">
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<li id="fn:1" role="doc-endnote">
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<p>A Rosebrock. “PyTorch: Transfer Learning and Image Classification”. pyimagesearch.com.
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<a href="https://pyimagesearch.com/2021/10/11/pytorch-transfer-learning-and-image-classification/">https://pyimagesearch.com/2021/10/11/pytorch-transfer-learning-and-image-classification/</a> (accessed Mar. 1, 2022.) <a href="#fnref:1" class="footnote-backref" role="doc-backlink">↩︎</a></p>
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</li>
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<li id="fn:2" role="doc-endnote">
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<p>A Rosebrock. “Regression with Keras”. pyimagesearch.com.
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<a href="https://pyimagesearch.com/2019/01/21/regression-with-keras/">https://pyimagesearch.com/2019/01/21/regression-with-keras/</a> (accessed Feb. 22, 2022.) <a href="#fnref:2" class="footnote-backref" role="doc-backlink">↩︎</a></p>
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</li>
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<li id="fn:3" role="doc-endnote">
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<p>A Rosebrock. “Keras, Regression, and CNNs”. pyimagesearch.com.
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<a href="https://pyimagesearch.com/2019/01/28/keras-regression-and-cnns/">https://pyimagesearch.com/2019/01/28/keras-regression-and-cnns/</a> (accessed Feb. 22, 2022.) <a href="#fnref:3" class="footnote-backref" role="doc-backlink">↩︎</a></p>
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