Morten Hjorth-Jensen
373 lines
24 KiB
HTML
373 lines
24 KiB
HTML
<!--
|
||
HTML file automatically generated from DocOnce source
|
||
(https://github.com/doconce/doconce/)
|
||
doconce format html week44.do.txt --html_style=bootstrap --pygments_html_style=default --html_admon=bootstrap_panel --html_output=week44-bs --no_mako
|
||
-->
|
||
<html>
|
||
<head>
|
||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||
<meta name="generator" content="DocOnce: https://github.com/doconce/doconce/" />
|
||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||
<meta name="description" content="Week 44, Convolutional Neural Networks (CNN)">
|
||
<title>Week 44, Convolutional Neural Networks (CNN)</title>
|
||
<!-- Bootstrap style: bootstrap -->
|
||
<!-- doconce format html week44.do.txt --html_style=bootstrap --pygments_html_style=default --html_admon=bootstrap_panel --html_output=week44-bs --no_mako -->
|
||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||
<!-- not necessary
|
||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||
-->
|
||
<style type="text/css">
|
||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||
.dropdown-menu {
|
||
height: auto;
|
||
max-height: 400px;
|
||
overflow-x: hidden;
|
||
}
|
||
/* Adds an invisible element before each target to offset for the navigation
|
||
bar */
|
||
.anchor::before {
|
||
content:"";
|
||
display:block;
|
||
height:50px; /* fixed header height for style bootstrap */
|
||
margin:-50px 0 0; /* negative fixed header height */
|
||
}
|
||
</style>
|
||
</head>
|
||
|
||
<!-- tocinfo
|
||
{'highest level': 2,
|
||
'sections': [('Plan for week 44', 2, None, 'plan-for-week-44'),
|
||
('Lab sessions on Tuesday and Wednesday',
|
||
2,
|
||
None,
|
||
'lab-sessions-on-tuesday-and-wednesday'),
|
||
('Material for Lecture Monday October 28',
|
||
2,
|
||
None,
|
||
'material-for-lecture-monday-october-28'),
|
||
('Convolutional Neural Networks (recognizing images)',
|
||
2,
|
||
None,
|
||
'convolutional-neural-networks-recognizing-images'),
|
||
('What is the Difference', 2, None, 'what-is-the-difference'),
|
||
('Neural Networks vs CNNs', 2, None, 'neural-networks-vs-cnns'),
|
||
('Why CNNS for images, sound files, medical images from CT scans '
|
||
'etc?',
|
||
2,
|
||
None,
|
||
'why-cnns-for-images-sound-files-medical-images-from-ct-scans-etc'),
|
||
('Regular NNs don’t scale well to full images',
|
||
2,
|
||
None,
|
||
'regular-nns-don-t-scale-well-to-full-images'),
|
||
('3D volumes of neurons', 2, None, '3d-volumes-of-neurons'),
|
||
('More on Dimensionalities', 2, None, 'more-on-dimensionalities'),
|
||
('Further remarks', 2, None, 'further-remarks'),
|
||
('Layers used to build CNNs',
|
||
2,
|
||
None,
|
||
'layers-used-to-build-cnns'),
|
||
('Transforming images', 2, None, 'transforming-images'),
|
||
('CNNs in brief', 2, None, 'cnns-in-brief'),
|
||
('A deep CNN model ("From Raschka et '
|
||
'al":"https://github.com/rasbt/machine-learning-book")',
|
||
2,
|
||
None,
|
||
'a-deep-cnn-model-from-raschka-et-al-https-github-com-rasbt-machine-learning-book'),
|
||
('Key Idea', 2, None, 'key-idea'),
|
||
('Mathematics of CNNs', 2, None, 'mathematics-of-cnns'),
|
||
('Convolution Examples: Polynomial multiplication',
|
||
2,
|
||
None,
|
||
'convolution-examples-polynomial-multiplication'),
|
||
('Efficient Polynomial Multiplication',
|
||
2,
|
||
None,
|
||
'efficient-polynomial-multiplication'),
|
||
('Further simplification', 2, None, 'further-simplification'),
|
||
('A more efficient way of coding the above Convolution',
|
||
2,
|
||
None,
|
||
'a-more-efficient-way-of-coding-the-above-convolution'),
|
||
('Fourier series and Toeplitz matrices',
|
||
2,
|
||
None,
|
||
'fourier-series-and-toeplitz-matrices'),
|
||
('Generalizing the above one-dimensional case',
|
||
2,
|
||
None,
|
||
'generalizing-the-above-one-dimensional-case'),
|
||
('Two-dimensional Objects', 2, None, 'two-dimensional-objects'),
|
||
('CNNs in more detail', 2, None, 'cnns-in-more-detail'),
|
||
('Performing a discrete convolution with padding ("From Raschka '
|
||
'et al":"https://github.com/rasbt/machine-learning-book")',
|
||
2,
|
||
None,
|
||
'performing-a-discrete-convolution-with-padding-from-raschka-et-al-https-github-com-rasbt-machine-learning-book'),
|
||
('Performing a general discrete convolution ("From Raschka et '
|
||
'al":"https://github.com/rasbt/machine-learning-book")',
|
||
2,
|
||
None,
|
||
'performing-a-general-discrete-convolution-from-raschka-et-al-https-github-com-rasbt-machine-learning-book'),
|
||
('Set of filters', 2, None, 'set-of-filters'),
|
||
('Pooling', 2, None, 'pooling'),
|
||
('No zero padding, unit strides',
|
||
2,
|
||
None,
|
||
'no-zero-padding-unit-strides'),
|
||
('Zero padding, unit strides',
|
||
2,
|
||
None,
|
||
'zero-padding-unit-strides'),
|
||
('Half (same) padding', 2, None, 'half-same-padding'),
|
||
('Full padding', 2, None, 'full-padding'),
|
||
('Pooling arithmetic', 2, None, 'pooling-arithmetic'),
|
||
('Pooling types ("From Raschka et '
|
||
'al":"https://github.com/rasbt/machine-learning-book")',
|
||
2,
|
||
None,
|
||
'pooling-types-from-raschka-et-al-https-github-com-rasbt-machine-learning-book'),
|
||
('Building our own CNN code',
|
||
2,
|
||
None,
|
||
'building-our-own-cnn-code'),
|
||
('List of contents:', 3, None, 'list-of-contents'),
|
||
('Schedulers', 3, None, 'schedulers'),
|
||
('Usage of schedulers', 3, None, 'usage-of-schedulers'),
|
||
('Cost functions', 3, None, 'cost-functions'),
|
||
('Usage of cost functions', 3, None, 'usage-of-cost-functions'),
|
||
('Activation functions', 3, None, 'activation-functions'),
|
||
('Usage of activation functions',
|
||
3,
|
||
None,
|
||
'usage-of-activation-functions'),
|
||
('Convolution', 3, None, 'convolution'),
|
||
('Layers', 3, None, 'layers'),
|
||
('Convolution2DLayer: convolution in a hidden layer',
|
||
3,
|
||
None,
|
||
'convolution2dlayer-convolution-in-a-hidden-layer'),
|
||
('Backpropagation in the convolutional layer',
|
||
3,
|
||
None,
|
||
'backpropagation-in-the-convolutional-layer'),
|
||
('Demonstration', 3, None, 'demonstration'),
|
||
('Pooling Layer', 3, None, 'pooling-layer'),
|
||
('Flattening Layer', 3, None, 'flattening-layer'),
|
||
('Fully Connected Layers', 3, None, 'fully-connected-layers'),
|
||
('Optimized Convolution2DLayer',
|
||
3,
|
||
None,
|
||
'optimized-convolution2dlayer'),
|
||
('The Convolutional Neural Network (CNN)',
|
||
3,
|
||
None,
|
||
'the-convolutional-neural-network-cnn'),
|
||
('Usage of CNN code', 3, None, 'usage-of-cnn-code'),
|
||
('Additional Remarks', 3, None, 'additional-remarks'),
|
||
('Remarks on the speed', 3, None, 'remarks-on-the-speed'),
|
||
('Convolution using separable kernels',
|
||
3,
|
||
None,
|
||
'convolution-using-separable-kernels'),
|
||
('Convolution in the Fourier domain',
|
||
3,
|
||
None,
|
||
'convolution-in-the-fourier-domain'),
|
||
('Building convolutional neural networks in Tensorflow and Keras',
|
||
2,
|
||
None,
|
||
'building-convolutional-neural-networks-in-tensorflow-and-keras'),
|
||
('Setting it up', 2, None, 'setting-it-up'),
|
||
('The MNIST dataset again', 2, None, 'the-mnist-dataset-again'),
|
||
('Strong correlations', 2, None, 'strong-correlations'),
|
||
('Layers of a CNN', 2, None, 'layers-of-a-cnn'),
|
||
('Systematic reduction', 2, None, 'systematic-reduction'),
|
||
('Prerequisites: Collect and pre-process data',
|
||
2,
|
||
None,
|
||
'prerequisites-collect-and-pre-process-data'),
|
||
('Importing Keras and Tensorflow',
|
||
2,
|
||
None,
|
||
'importing-keras-and-tensorflow'),
|
||
('Running with Keras', 2, None, 'running-with-keras'),
|
||
('Final part', 2, None, 'final-part'),
|
||
('Final visualization', 2, None, 'final-visualization')]}
|
||
end of tocinfo -->
|
||
|
||
<body>
|
||
|
||
|
||
|
||
<script type="text/x-mathjax-config">
|
||
MathJax.Hub.Config({
|
||
TeX: {
|
||
equationNumbers: { autoNumber: "none" },
|
||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||
}
|
||
});
|
||
</script>
|
||
<script type="text/javascript" async
|
||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||
</script>
|
||
|
||
|
||
<!-- Bootstrap navigation bar -->
|
||
<div class="navbar navbar-default navbar-fixed-top">
|
||
<div class="navbar-header">
|
||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||
<span class="icon-bar"></span>
|
||
<span class="icon-bar"></span>
|
||
<span class="icon-bar"></span>
|
||
</button>
|
||
<a class="navbar-brand" href="week44-bs.html">Week 44, Convolutional Neural Networks (CNN)</a>
|
||
</div>
|
||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||
<ul class="nav navbar-nav navbar-right">
|
||
<li class="dropdown">
|
||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||
<ul class="dropdown-menu">
|
||
<!-- navigation toc: --> <li><a href="._week44-bs001.html#plan-for-week-44" style="font-size: 80%;"><b>Plan for week 44</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs002.html#lab-sessions-on-tuesday-and-wednesday" style="font-size: 80%;"><b>Lab sessions on Tuesday and Wednesday</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs003.html#material-for-lecture-monday-october-28" style="font-size: 80%;"><b>Material for Lecture Monday October 28</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs004.html#convolutional-neural-networks-recognizing-images" style="font-size: 80%;"><b>Convolutional Neural Networks (recognizing images)</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs005.html#what-is-the-difference" style="font-size: 80%;"><b>What is the Difference</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs006.html#neural-networks-vs-cnns" style="font-size: 80%;"><b>Neural Networks vs CNNs</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs007.html#why-cnns-for-images-sound-files-medical-images-from-ct-scans-etc" style="font-size: 80%;"><b>Why CNNS for images, sound files, medical images from CT scans etc?</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs008.html#regular-nns-don-t-scale-well-to-full-images" style="font-size: 80%;"><b>Regular NNs don’t scale well to full images</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs009.html#3d-volumes-of-neurons" style="font-size: 80%;"><b>3D volumes of neurons</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs010.html#more-on-dimensionalities" style="font-size: 80%;"><b>More on Dimensionalities</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs011.html#further-remarks" style="font-size: 80%;"><b>Further remarks</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs012.html#layers-used-to-build-cnns" style="font-size: 80%;"><b>Layers used to build CNNs</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs013.html#transforming-images" style="font-size: 80%;"><b>Transforming images</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs014.html#cnns-in-brief" style="font-size: 80%;"><b>CNNs in brief</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs015.html#a-deep-cnn-model-from-raschka-et-al-https-github-com-rasbt-machine-learning-book" style="font-size: 80%;"><b>A deep CNN model ("From Raschka et al":"https://github.com/rasbt/machine-learning-book")</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs016.html#key-idea" style="font-size: 80%;"><b>Key Idea</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs017.html#mathematics-of-cnns" style="font-size: 80%;"><b>Mathematics of CNNs</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs018.html#convolution-examples-polynomial-multiplication" style="font-size: 80%;"><b>Convolution Examples: Polynomial multiplication</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs019.html#efficient-polynomial-multiplication" style="font-size: 80%;"><b>Efficient Polynomial Multiplication</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs020.html#further-simplification" style="font-size: 80%;"><b>Further simplification</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs021.html#a-more-efficient-way-of-coding-the-above-convolution" style="font-size: 80%;"><b>A more efficient way of coding the above Convolution</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs022.html#fourier-series-and-toeplitz-matrices" style="font-size: 80%;"><b>Fourier series and Toeplitz matrices</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs023.html#generalizing-the-above-one-dimensional-case" style="font-size: 80%;"><b>Generalizing the above one-dimensional case</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs023.html#two-dimensional-objects" style="font-size: 80%;"><b>Two-dimensional Objects</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs024.html#cnns-in-more-detail" style="font-size: 80%;"><b>CNNs in more detail</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs025.html#performing-a-discrete-convolution-with-padding-from-raschka-et-al-https-github-com-rasbt-machine-learning-book" style="font-size: 80%;"><b>Performing a discrete convolution with padding ("From Raschka et al":"https://github.com/rasbt/machine-learning-book")</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs026.html#performing-a-general-discrete-convolution-from-raschka-et-al-https-github-com-rasbt-machine-learning-book" style="font-size: 80%;"><b>Performing a general discrete convolution ("From Raschka et al":"https://github.com/rasbt/machine-learning-book")</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs027.html#set-of-filters" style="font-size: 80%;"><b>Set of filters</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs028.html#pooling" style="font-size: 80%;"><b>Pooling</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs029.html#no-zero-padding-unit-strides" style="font-size: 80%;"><b>No zero padding, unit strides</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs030.html#zero-padding-unit-strides" style="font-size: 80%;"><b>Zero padding, unit strides</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs031.html#half-same-padding" style="font-size: 80%;"><b>Half (same) padding</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs032.html#full-padding" style="font-size: 80%;"><b>Full padding</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs033.html#pooling-arithmetic" style="font-size: 80%;"><b>Pooling arithmetic</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs034.html#pooling-types-from-raschka-et-al-https-github-com-rasbt-machine-learning-book" style="font-size: 80%;"><b>Pooling types ("From Raschka et al":"https://github.com/rasbt/machine-learning-book")</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#building-our-own-cnn-code" style="font-size: 80%;"><b>Building our own CNN code</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#list-of-contents" style="font-size: 80%;"> List of contents:</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#schedulers" style="font-size: 80%;"> Schedulers</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#usage-of-schedulers" style="font-size: 80%;"> Usage of schedulers</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#cost-functions" style="font-size: 80%;"> Cost functions</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#usage-of-cost-functions" style="font-size: 80%;"> Usage of cost functions</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#activation-functions" style="font-size: 80%;"> Activation functions</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#usage-of-activation-functions" style="font-size: 80%;"> Usage of activation functions</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#convolution" style="font-size: 80%;"> Convolution</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#layers" style="font-size: 80%;"> Layers</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#convolution2dlayer-convolution-in-a-hidden-layer" style="font-size: 80%;"> Convolution2DLayer: convolution in a hidden layer</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#backpropagation-in-the-convolutional-layer" style="font-size: 80%;"> Backpropagation in the convolutional layer</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#demonstration" style="font-size: 80%;"> Demonstration</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#pooling-layer" style="font-size: 80%;"> Pooling Layer</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#flattening-layer" style="font-size: 80%;"> Flattening Layer</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#fully-connected-layers" style="font-size: 80%;"> Fully Connected Layers</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#optimized-convolution2dlayer" style="font-size: 80%;"> Optimized Convolution2DLayer</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#the-convolutional-neural-network-cnn" style="font-size: 80%;"> The Convolutional Neural Network (CNN)</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#usage-of-cnn-code" style="font-size: 80%;"> Usage of CNN code</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#additional-remarks" style="font-size: 80%;"> Additional Remarks</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#remarks-on-the-speed" style="font-size: 80%;"> Remarks on the speed</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#convolution-using-separable-kernels" style="font-size: 80%;"> Convolution using separable kernels</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs035.html#convolution-in-the-fourier-domain" style="font-size: 80%;"> Convolution in the Fourier domain</a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs036.html#building-convolutional-neural-networks-in-tensorflow-and-keras" style="font-size: 80%;"><b>Building convolutional neural networks in Tensorflow and Keras</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs037.html#setting-it-up" style="font-size: 80%;"><b>Setting it up</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs038.html#the-mnist-dataset-again" style="font-size: 80%;"><b>The MNIST dataset again</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs039.html#strong-correlations" style="font-size: 80%;"><b>Strong correlations</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs040.html#layers-of-a-cnn" style="font-size: 80%;"><b>Layers of a CNN</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs041.html#systematic-reduction" style="font-size: 80%;"><b>Systematic reduction</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs042.html#prerequisites-collect-and-pre-process-data" style="font-size: 80%;"><b>Prerequisites: Collect and pre-process data</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs043.html#importing-keras-and-tensorflow" style="font-size: 80%;"><b>Importing Keras and Tensorflow</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs044.html#running-with-keras" style="font-size: 80%;"><b>Running with Keras</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs045.html#final-part" style="font-size: 80%;"><b>Final part</b></a></li>
|
||
<!-- navigation toc: --> <li><a href="._week44-bs046.html#final-visualization" style="font-size: 80%;"><b>Final visualization</b></a></li>
|
||
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</div>
|
||
</div>
|
||
</div> <!-- end of navigation bar -->
|
||
<div class="container">
|
||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||
<a name="part0000"></a>
|
||
<!-- ------------------- main content ---------------------- -->
|
||
<div class="jumbotron">
|
||
<center>
|
||
<h1>Week 44, Convolutional Neural Networks (CNN)</h1>
|
||
</center> <!-- document title -->
|
||
|
||
<!-- author(s): Morten Hjorth-Jensen -->
|
||
<center>
|
||
<b>Morten Hjorth-Jensen</b> [1, 2]
|
||
</center>
|
||
<!-- institution(s) -->
|
||
<center>
|
||
[1] <b>Department of Physics, University of Oslo</b>
|
||
</center>
|
||
<center>
|
||
[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b>
|
||
</center>
|
||
<br>
|
||
<center>
|
||
<h4>October 28-November 1 </h4>
|
||
</center> <!-- date -->
|
||
<br>
|
||
|
||
|
||
|
||
<p><a href="._week44-bs001.html" class="btn btn-primary btn-lg">Read »</a></p>
|
||
|
||
|
||
</div> <!-- end jumbotron -->
|
||
|
||
<p>
|
||
<!-- navigation buttons at the bottom of the page -->
|
||
<ul class="pagination">
|
||
<li class="active"><a href="._week44-bs000.html">1</a></li>
|
||
<li><a href="._week44-bs001.html">2</a></li>
|
||
<li><a href="._week44-bs002.html">3</a></li>
|
||
<li><a href="._week44-bs003.html">4</a></li>
|
||
<li><a href="._week44-bs004.html">5</a></li>
|
||
<li><a href="._week44-bs005.html">6</a></li>
|
||
<li><a href="._week44-bs006.html">7</a></li>
|
||
<li><a href="._week44-bs007.html">8</a></li>
|
||
<li><a href="._week44-bs008.html">9</a></li>
|
||
<li><a href="._week44-bs009.html">10</a></li>
|
||
<li><a href="">...</a></li>
|
||
<li><a href="._week44-bs046.html">47</a></li>
|
||
<li><a href="._week44-bs001.html">»</a></li>
|
||
</ul>
|
||
<!-- ------------------- end of main content --------------- -->
|
||
</div> <!-- end container -->
|
||
<!-- include javascript, jQuery *first* -->
|
||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||
<!-- Bootstrap footer
|
||
<footer>
|
||
<a href="https://..."><img width="250" align=right src="https://..."></a>
|
||
</footer>
|
||
-->
|
||
<center style="font-size:80%">
|
||
<!-- copyright --> © 1999-2024, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
|
||
</center>
|
||
</body>
|
||
</html>
|
||
|