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Rethinking Atreus Convolution for Semantic Image Segmentation George Papandreou Florian Scoff Hart wig Adam Google Inc. lichen, Japan, Ashcroft, Adam google.com arXiv:1706.05587v1 cs. CV 17 Jun 2017
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Step 1: Understand the concept of atrous convolution and its benefits.
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Researchers in computer vision who wish to improve the performance of convolutional neural networks.
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Rethinking atrous convolution is used to improve the efficiency and performance of convolutional neural networks.
Research scientists, machine learning engineers, and developers working on computer vision tasks may need to implement rethinking atrous convolution.
To fill out rethinking atrous convolution, one must understand the concept of dilated convolutions and how to apply them in deep learning models.
The purpose of rethinking atrous convolution is to increase the receptive field of neural networks without increasing the number of parameters, thus improving feature extraction.
Information on the network architecture, dilation rates, and implementation details must be reported on rethinking atrous convolution.
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