Join the professional CV group of Jishi, interact with 6000+ visual developers from top companies and universities such as Tencent, Huawei, Baidu, Peking University, Tsinghua University, and the Chinese Academy of Sciences! There is also an opportunity to interact with Professor Kai-Fu Lee and other experts! We also provide monthly expert live sharing, real project … Read more
【Introduction】The traditional visual recognition methods struggle to directly distinguish between NIs (Natural Images) and CG (Computer Generated images). This article proposes an efficient image recognition method based on Convolutional Neural Networks (CNNs). A large number of experiments were conducted to evaluate the model’s performance. The experimental results show that this method outperforms existing recognition methods … Read more
Click on the above “AI Youdao“, select “Star” public account Heavyweight content delivered first time Author | Raimi Karim Translator | Major Editor | Zhao Xue Produced by | AI Technology Camp (ID: rgznai100) Introduction: In recent years, many Convolutional Neural Networks (CNN) have come into the spotlight, and as their depths become increasingly profound, … Read more
100 Questions on Deep Learning Author: louwill Machine Learning Lab The MobileNet series, as a representative of lightweight networks, makes the lightweight deployment of CNNs on mobile devices possible. Currently, there are three versions of MobileNet: MobileNet v1, MobileNet v2, and MobileNet v3. This article focuses on elaborating the MobileNet series networks, which is essential … Read more
Click Machine Learning Algorithms and Python Learning ，Select Star Don’t miss out on the wonderful content Author | Raimi Karim, Produced by | AI Technology Camp (ID: rgznai100) This article carefully selects 10 detailed diagrams of CNN architectures for discussion. Curated by the author. These diagrams showcase the essence of the entire model without the … Read more
01 Introduction This article reviews some of the more ingeniously designed and practical “plugins” used in CNN networks. The so-called “plugins” are modules that do not alter the main structure of the network and can be easily integrated into mainstream networks to enhance their feature extraction capabilities, achieving a plug-and-play functionality. Many similar reviews claim … Read more
Selected from offconvex Author：John Miller Translated by Machine Heart Contributors: Qianshu, Zhang Qian, Siyuan In recent years, while Recurrent Neural Networks (RNNs) have been dominant, models like autoregressive Wavenet or Transformers are now replacing RNNs in various sequence modeling tasks. Machine Heart has previously introduced RNNs and CNNs for sequence modeling in a GitHub project, … Read more
Author: Huang Yu, Autonomous Driving Scientist Editor: Hoh Xil Source: Huang Yu@Zhihu Produced by: DataFunTalk Note: There is a latest autonomous driving salon at the end of the article, welcome to sign up. Introduction: Deep learning has been “hot” for more than ten years since 2006, and the most common applications we see are in … Read more
Selected from GitHub Author: Shuai Zheng et al. Translated by: Machine Heart Contributors: Jiang Siyuan This GitHub project implements image semantic segmentation by combining CNN and CRF-RNN models. Readers can follow this project to implement the process using Keras/Tensorflow. Demo Address: http://crfasrnn.torr.vision Project Address: https://github.com/sadeepj/crfasrnn_keras This GitHub project contains methods to implement “CRF-RNN” image semantic … Read more
Author | Bill Vorhies Translator | Gai Lei Editor | Vincent AI Frontline Overview: From some interesting use cases, it seems we can completely combine CNN and RNN/LSTM. Many researchers are currently working on this research. However, the latest research trends in CNN may render this idea outdated. For more quality content, please follow the … Read more