Abstract: Divide-and-conquer approach towards understanding deep networks

Abstract

Deep neural networks have achieved tremendous success in various fields including medical image segmentation. However, they have long been criticized for being a black-box, in that interpretation, understanding and correcting architectures is diffcult as there is no general theory for deep neural network design. Previously, precision learning was proposed to fuse deep architectures and traditional approaches.