quarter CNN: Deep Residual Network скачать в хорошем качестве

quarter CNN: Deep Residual Network

This video introduces the deep residual network published in the paper entitled “Deep Residual Learning for Image Classification”, by Kaiming He in CVPR 2016. The outline of this lecture includes: (1) Introduction about the depth evolution in the literature of neural networks and the issue to be addressed when the neural network uses more layers. (2) Deep residual network about the main idea of the proposed deep residual network, the layout of the residual block, and the architecture of the proposed deep residual network. (3) Deeper residual network about the bottleneck block for building the deeper residual network and its architecture. 00:00 Introduction 01:34 Evolution of Depth 02:26 Issue for More Layers 04:32 Deep Residual Network 07:04 Residual Block 11:54 Network Architecture 16:43 Bottleneck Residual Block 20:07 Network Architecture Any comments are welcome. (email: [email protected]) All resources are available on the website (https://powwhuang.github.io/quarter_www/)