INet: Convolutional Networks for Biomedical Image Segmentation

Encoder-decoder networks are state-of-the-art approaches to biomedical image segmentation, but have two problems: i.e., the widely used pooling operations may discard spatial information, and therefore low-level semantics are lost. Feature fusion methods can mitigate these problems but feature maps...

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