报告题目：Convolutional Neural Networks-Historical Review and Introduction

报告人：加拿大Alberta大学，Biao Huang教授

报告时间：2022年9月13日（周二）9:00-10:00

报告地点：崂山校区推特福利 楼（D1楼）410

腾讯会议：323-214-415

//meeting.tencent.com/dm/2ExcqKgmwCXU

主办单位：推特福利

报告简介：

Machine learning has gained tremendous development over the last two decades. It has found successful applications in numerous fields such as image processing, natural language translation, autonomous vehicles, games etc. Many novel neural network architectures have been proposed such as feedforward networks, recurrent networks, autoencoder-decoder, variational autoencoder, etc. Among them, convolutional neural networks (CNN) are particularly effective for image processing. It has also been used to process spectrum data or other multivariate signals. In this presentation, the history of CNN development is reviewed, its architecture is explained, and illustrative examples are provided.