设为首页 | 加入收藏 | 宁波大学
数学与统计学院
首页学院概况师资队伍科学研究人才培养党员之家学生工作中外合作办学校友之家招聘信息信息公开English
新闻中心
 学院新闻 
 通知通告 
 学术活动 
 学生工作 
 人才培养 
 
当前位置: 首页>>新闻中心>>学术活动>>正文
甬江数学讲坛214讲(2021年第73讲)
2021-12-08 18:26     (点击:)

报告题目:Sensor-Based Activity Recognition via Kernel-embedding Neural Networks

报 告 人:Sinno Jialin Pan (新加坡南洋理工大学 教授)

会议时间:2021/12/14(周二) 上午10:00开始

会议地点:线上,腾讯会议号: 380 645 135

报告摘要:Feature-engineering-based machine learning models and deep learning models have been explored for wearable-sensor-based human activity recognition. For both types of methods, one crucial research issue is how to extract proper features from the partitioned segments of multivariate sensor readings. Existing methods have different drawbacks: 1) feature-engineering-based methods are able to extract meaningful features, such as statistical or structural information underlying the segments, but usually require manual designs of features for different applications, which is time consuming, and 2) deep learning models are able to learn temporal and/or spatial features from the sensor data automatically, but fail to capture statistical information. In this talk, I will introduce our recently developed kernel-embedding neural architecture that is able to automatically learn meaningful features including statistical features, temporal features and spatial correlation features for activity recognition. I will also discuss some advanced issues in sensor-based activity recognition.

报告人简介:Sinno Jialin Pan is a Provosts Chair Associate Professor with the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He received his Ph.D. degree in computer science from the Hong Kong University of Science and Technology (HKUST) in 2011. Prior to joining NTU, he was a scientist and Lab Head of text analytics with the Data Analytics Department at Institute for Infocomm Research, Singapore. He joined NTU as a Nanyang Assistant Professor in 2014. He was named to the list of AI 10 to Watch by the IEEE Intelligent Systems magazine in 2018. He serves as an Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Artificial Intelligence (AIJ) and ACM Transactions on Intelligent Systems and Technology (TIST). His research interests include transfer learning and its real-world applications.

 

 

关闭窗口
宁波大学 | 图书馆

地址:宁波市江北区风华路818号宁波大学包玉书9号楼;邮编:315211;电话:0574-87600795