Morten Hjorth-Jensen
294 lines
16 KiB
HTML
294 lines
16 KiB
HTML
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<a class="navbar-brand" href="week44-bs.html">Week 44, Convolutional Neural Networks (CNN)</a>
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<!-- navigation toc: --> <li><a href="._week44-bs001.html#plan-for-week-44" style="font-size: 80%;">Plan for week 44</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs002.html#material-for-lecture-thursday-november-2" style="font-size: 80%;">Material for Lecture Thursday November 2</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs003.html#convolutional-neural-networks-recognizing-images" style="font-size: 80%;">Convolutional Neural Networks (recognizing images)</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs004.html#what-is-the-difference" style="font-size: 80%;">What is the Difference</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs005.html#neural-networks-vs-cnns" style="font-size: 80%;">Neural Networks vs CNNs</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs006.html#why-cnns-for-images-sound-files-medical-images-from-ct-scans-etc" style="font-size: 80%;">Why CNNS for images, sound files, medical images from CT scans etc?</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs007.html#regular-nns-don-t-scale-well-to-full-images" style="font-size: 80%;">Regular NNs don’t scale well to full images</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs008.html#3d-volumes-of-neurons" style="font-size: 80%;">3D volumes of neurons</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs009.html#layers-used-to-build-cnns" style="font-size: 80%;">Layers used to build CNNs</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs010.html#transforming-images" style="font-size: 80%;">Transforming images</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs011.html#cnns-in-brief" style="font-size: 80%;">CNNs in brief</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs012.html#key-idea" style="font-size: 80%;">Key Idea</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs013.html#mathematics-of-cnns" style="font-size: 80%;">Mathematics of CNNs</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs014.html#convolution-examples-polynomial-multiplication" style="font-size: 80%;">Convolution Examples: Polynomial multiplication</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs015.html#efficient-polynomial-multiplication" style="font-size: 80%;">Efficient Polynomial Multiplication</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs016.html#a-more-efficient-way-of-coding-the-above-convolution" style="font-size: 80%;">A more efficient way of coding the above Convolution</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs017.html#convolution-examples-principle-of-superposition-and-periodic-forces-fourier-transforms" style="font-size: 80%;">Convolution Examples: Principle of Superposition and Periodic Forces (Fourier Transforms)</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs018.html#principle-of-superposition" style="font-size: 80%;">Principle of Superposition</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs019.html#simple-code-example" style="font-size: 80%;">Simple Code Example</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs020.html#wrapping-up-fourier-transforms" style="font-size: 80%;">Wrapping up Fourier transforms</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs021.html#finding-the-coefficients" style="font-size: 80%;">Finding the Coefficients</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs022.html#final-words-on-fourier-transforms" style="font-size: 80%;">Final words on Fourier Transforms</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs023.html#two-dimensional-objects" style="font-size: 80%;">Two-dimensional Objects</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs024.html#cross-correlation" style="font-size: 80%;">Cross-Correlation</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs025.html#more-on-dimensionalities" style="font-size: 80%;">More on Dimensionalities</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs026.html#further-dimensionality-remarks" style="font-size: 80%;">Further Dimensionality Remarks</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs027.html#cnns-in-more-detail-lecture-from-in5400" style="font-size: 80%;">CNNs in more detail, Lecture from IN5400</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs028.html#cnns-in-more-detail-building-convolutional-neural-networks-in-tensorflow-and-keras" style="font-size: 80%;">CNNs in more detail, building convolutional neural networks in Tensorflow and Keras</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs029.html#setting-it-up" style="font-size: 80%;">Setting it up</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs030.html#the-mnist-dataset-again" style="font-size: 80%;">The MNIST dataset again</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs031.html#strong-correlations" style="font-size: 80%;">Strong correlations</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs032.html#layers-of-a-cnn" style="font-size: 80%;">Layers of a CNN</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs033.html#systematic-reduction" style="font-size: 80%;">Systematic reduction</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs034.html#prerequisites-collect-and-pre-process-data" style="font-size: 80%;">Prerequisites: Collect and pre-process data</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs035.html#importing-keras-and-tensorflow" style="font-size: 80%;">Importing Keras and Tensorflow</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs036.html#running-with-keras" style="font-size: 80%;">Running with Keras</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs037.html#final-part" style="font-size: 80%;">Final part</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs038.html#final-visualization" style="font-size: 80%;">Final visualization</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs039.html#the-cifar01-data-set" style="font-size: 80%;">The CIFAR01 data set</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs040.html#verifying-the-data-set" style="font-size: 80%;">Verifying the data set</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs041.html#set-up-the-model" style="font-size: 80%;">Set up the model</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs042.html#add-dense-layers-on-top" style="font-size: 80%;">Add Dense layers on top</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs043.html#compile-and-train-the-model" style="font-size: 80%;">Compile and train the model</a></li>
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<!-- navigation toc: --> <li><a href="._week44-bs044.html#finally-evaluate-the-model" style="font-size: 80%;">Finally, evaluate the model</a></li>
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<!-- ------------------- main content ---------------------- -->
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<center>
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<h1>Week 44, Convolutional Neural Networks (CNN)</h1>
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</center> <!-- document title -->
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<!-- author(s): Morten Hjorth-Jensen -->
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<center>
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<b>Morten Hjorth-Jensen</b> [1, 2]
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</center>
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<!-- institution(s) -->
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<center>
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[1] <b>Department of Physics, University of Oslo</b>
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<center>
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[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b>
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</center>
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<br>
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<center>
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<h4>October 30-November 3</h4>
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</center> <!-- date -->
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<br>
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<p><a href="._week44-bs001.html" class="btn btn-primary btn-lg">Read »</a></p>
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<li class="active"><a href="._week44-bs000.html">1</a></li>
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<li><a href="._week44-bs001.html">2</a></li>
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<li><a href="._week44-bs002.html">3</a></li>
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<li><a href="._week44-bs003.html">4</a></li>
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<li><a href="._week44-bs004.html">5</a></li>
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<li><a href="._week44-bs005.html">6</a></li>
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<li><a href="._week44-bs006.html">7</a></li>
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<li><a href="._week44-bs007.html">8</a></li>
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<li><a href="._week44-bs008.html">9</a></li>
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<li><a href="._week44-bs009.html">10</a></li>
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<li><a href="">...</a></li>
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<li><a href="._week44-bs044.html">45</a></li>
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<li><a href="._week44-bs001.html">»</a></li>
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