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	<title>Tensorflow Archives &#8212; MATLAB Number ONE</title>
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		<title>Training the MNIST model in Keras</title>
		<link>https://matlab1.com/shop/python-code/training-the-mnist-model-in-keras/</link>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Fri, 08 Jun 2018 17:38:43 +0000</pubDate>
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					<description><![CDATA[<p>In this product, we will use the model using tf.keras APIs. It is better to learn both Keras and layers packages from TensorFlow as they could be seen at several open source codes. The objective of the product is to make you understand various offerings of TensorFlow so that you can build products on top of it.  &#8220;Code [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/python-code/training-the-mnist-model-in-keras/">Training the MNIST model in Keras</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Python code for Vehicle Make Detection by Convolutional Neural Networks</title>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 03 Apr 2018 07:32:46 +0000</pubDate>
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					<description><![CDATA[<p>&#160; For car make identification, we first came up with using the SIFT descriptor and SIFT matching with RANSAC. The matching results of two images from Hyundai Sonata are shown in Figure 1. From Figure 5, we observe that only a very few points get matched while those points don’t indicate the same feature on the vehicle. SIFT matching is robust [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/python-code/python-code-for-vehicle-make-detection-by-convolutional-neural-networks/">Python code for Vehicle Make Detection by Convolutional Neural Networks</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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