One Kernel to Solve Nearly Everything: Unified 3D Binary Convolutions for Image Analysis

MIDL 2018 MP HeinrichO OktayN Bouteldja

Deep networks have set the state-of-the-art in most image analysis tasks by replacing handcrafted features with learned convolution filters within end-to-end trainable architectures. Still, the specifications of a convolutional network are subject to much manual design - the shape and size of the receptive field for convolutional operations is a very sensitive part that has to be tuned for different image analysis applications... (read more)

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