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PyCodes.html
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<!DOCTYPE HTML>
<!--
Theory by TEMPLATED
templated.co @templatedco
Released for free under the Creative Commons Attribution 3.0 license (templated.co/license)
-->
<html>
<head>
<title>Python codes</title>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link rel="stylesheet" href="assets/css/main.css" />
<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-121835545-2"></script>
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window.dataLayer = window.dataLayer || [];
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gtag('js', new Date());
gtag('config', 'UA-121835545-2');
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<body>
<!-- Header -->
<header id="header">
<div class="inner">
<nav id="nav">
<a href="index.html">Home</a>
<a href="PyCodes.html">Pycodes</a>
<a href="datasets.html">Datasets</a>
<a href="visual.html">Inside</a>
<a href="license.html">License</a>
</nav>
<a href="#navPanel" class="navPanelToggle"><span class="fa fa-bars"></span></a>
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<!-- Banner -->
<section id="banner">
<h1>Deep Learning for Remote Sensing Scene Classification</h1>
<h3>This work aims to explore how to boost the performance of small-scale convolutional neural networks</h3>
</section>
<!-- Three -->
<section id="two" class="wrapper">
<header class="align-center">
<h2>Python codes used in this work</h2>
</header>
<div class="align-center">
<p>Here, you can get access to the two versions of the Python codes. </br>
The following codes are just examples, and updates will be made available soon. </br>
Please, choose which one you want to use.</p>
<menu>
<label class="container">Keras
<input type="radio" name="radio" value="A" onclick = "populateData(event)">
<span class="checkmark"></span>
</label>
<label class="container">TensorFlow
<input type="radio" name="radio" value="B" onclick = "populateData(event)">
<span class="checkmark"></span>
</label>
</menu>
</div>
<div id="content" class="align-center">
<div id="imge">
<img src="images/UnilNet_TB_SAT4.png" alt="TB"/>
</div>
</div>
<div id="Keras">
<div class="inner">
<img src="images/UnilNet_TB_SAT4.png" alt="TB" height="70" width="49"/>
<img src="images/keras-logo-2018-large-1200.png" alt="KR" height="70" width="242"/>
<p> Keras: The Python Deep Learning library.</p>
<script src="https://gist.github.com/mlaib/f0a3a2b7b3563013d1d929b53de8a720.js"></script>
</div>
</div>
<div id="Tensorflow">
<div class="inner">
<img src="images/UnilNet_TB_SAT4.png" alt="TB" height="70" width="49"/>
<img src="images/logo_TF.png" alt="UN" height="70" width="70"/>
<p> TensorFlow: An open-source machine learning framework for everyone.</p>
<script src="https://gist.github.com/jeangolay/40e9a72b31dbee46c40fc3cf2059dc19.js"></script>
</div>
</div>
<script>
var targetDiv = document.getElementById('content');
function populateData(event){
switch(event.target.value){
case 'A':{
document.getElementById("Keras").style.display = "inline";
document.getElementById("Tensorflow").style.display = "none";
document.getElementById("imge").style.display = "none";
break;
}
case 'B':{
document.getElementById("Keras").style.display = "none";
document.getElementById("Tensorflow").style.display = "inline";
document.getElementById("imge").style.display = "none";
break;
}
}
}
</script>
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© UnilNet | HTML template: <a href="https://templated.co">Templated.co</a> | Images: <a href="https://unsplash.com">Unsplash</a>.
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