Summary of Resnet Paper

This paper introduced a deep residual learning framework to ease the training of deep networks and showed that extreme deep residual nets are easy to optimize, but the counterpart "plain"...

Summary of Vggnet Paper

The authors experimented with different level of depths in convolutional neural networks (ConvNets) and presented the improvement in error reduction with respect to the depth. More non-linear rectification layers (ReLUs)...

Summary of AlexNet Paper

Alexnet is a deep neural network which learns visual knowledge from images to classify a given image. It had produced breakthrough results in ImageNet LSVRC-2010 contest achieving a top-1 error...