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]

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]

In this post, I would like to review the development of optimization methods for deep neural network (DNN) and share suggestions to use optimizers. What you can find: A brief review of the popular optimizers from the an intuitive perspective. The disadavantage of the popular adaptive optimizer, Adam.... [Read More]