Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Spatial pyramid pooling module or encode-decoder structure are used in deep neural networks for semantic segmentation task. The former networks are able to encode multi-scale contextual information by probing the incoming features with filters or pooling operations at multiple rates and multiple effective fields-of-view, while the latter networks can capture sharper object boundaries by gradually
How PyTorch Transposed Convs1D Work
WARNING: I’ll be assuming you know what neural networks and convolutional neural networks are. Also, this post is written in PyTorch (https://pytorch.org/) notation. Although it applies to the mentioned structures in any framework, it would be good to know the very basic syntax of pytorch to follow the few code snippets appearing creatings Tensors and layers. Hello there! I am a recurrent PyTorch
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