Selected from Medium Translated by Machine Heart Contributors: Lu Xue, Li Zenan Not long ago, Andrew Ng’s fourth course on Convolutional Neural Networks was released on Coursera. This article is a reflection written by Ryan Shrott, Chief Analyst at the National Bank of Canada, after completing the course, which helps everyone intuitively understand and learn … Read more
Click on the "Xiaobai Learns Vision" above, choose to add "Starred" or "Pinned" Heavyweight content delivered at the first time Introduction MoD is a new method for Convolutional Neural Networks (CNNs) that improves computational efficiency by selectively processing channels. Unlike traditional static pruning methods, MoD adopts a dynamic computation approach, adjusting computational resources based on … Read more
Technical Column Author: Liu Zhongyu Edited by Luobotu Today, I want to share with you about Graph Convolutional Networks. With the development of artificial intelligence, many people have heard of concepts like machine learning, deep learning, and convolutional neural networks. However, Graph Convolutional Networks are not often mentioned. So, what are Graph Convolutional Networks? Simply … Read more
Author: Zhang Xu Editor: Wang Shuwei This article has 4794 words and 27 images, reading time is about 11 minutes Forget it Read as long as you want Zero Reference Directory: 1. Convolutional Layer 1.1 The Role of Convolutional Layer in CNN 1.2 How Convolutional Layers Work 1.3 Convolutional Layers in AlexNet 2. Pooling and … Read more
AI World 2017 Opening Video The AI WORLD 2017 World Artificial Intelligence Conference, hosted by the new intelligence source AI news think tank, was held on November 8 at the National Convention Center in Beijing. The conference, themed ‘AI New Dimensions, China Intelligent+’, featured reports and discussions from over a hundred AI leaders covering the … Read more
Selected from The M Tank Translated by Machine Heart Contributors: Jiang Siyuan, Liu Xiaokun The M Tank has edited a report titled “A Year in Computer Vision,” documenting the research achievements in the field of computer vision from 2016 to 2017. This detailed material is invaluable for developers and researchers. The material consists of four … Read more