1. Introduction In this post, I write about reviews of some ResNet concerned paper, which includes ResNet, ResNeXt, SENet, SKNet, and ResNeSt. Since the publication of VGG net, lots of efforts are made to develop more efficient and more modular network backbone. The most popular 2 models are Inception... [Read More]

1. Introduction In this post, I resume the development of Inception network from V1 to V4. The main purpose of this post is to clearly state the development of design of Inception network. For better understanding of the history, I list the time of the publication of the 4... [Read More]

1. Introduction In this post, I’d like to review the 3 paper of YOLO. The main purpose is to understand the design of the YOLO and how the authors try to improve YOLO. For the details of implementation, such as learning rate and training tricks, please read the experiments... [Read More]

Paper to review: ImageNet Classification with Deep Convolutional Neural Networks Main contributions: Improve the architecture of CNN Realize GPU implementation of CNN The first CNN reaches best performance in ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) In the post of review of LeNet-5, Yann LuCun succeeded to implement... [Read More]

This post is a review of an old, difficult, and inspiring paper: Gradient-Based Learning Applied to Document Recognition”[1] by Yann LeCun as the first author. You can find many reviews of this paper. Most of them only focus on the architecture of the Convolution Neural Network (CNN) LeNet-5. However,... [Read More]