演讲摘要：Recent advances in image processing have made it possible to detect and track objects in video and imagery, but the focus has been on simple image recognition or tracking tasks, rather than end-to-end data analysis tasks. In this talk I will several end-to-end analytics applications built on imagery and video, including building maps from satellite imagery and running structured SQL queries over large archives of video. By taking an application centric view, we make several contributions back to the image processing domain, including novel iterative algorithms for tracing paths in images and adaptive algorithms for dramatically limiting the number of frames that need to be processed in object tracking applications.
讲者简介：Samuel Madden is a professor at MIT where he is the Schwartzman College of Computing Distinguished Professor of Computing. His research is in the area of database systems, focusing on database analytics and query processing, ranging from clouds to sensors to modern high-performance server architectures. He co-directs the Data Systems for AI Lab initiative and the Data Systems Group, investigating issues related to systems and algorithms for data focusing on applying new methodologies for processing data, including applying machine learning methods to data systems and engineering data systems for applying machine learning at scale.
Madden was named one of MIT Technology Review's "35 Innovators Under 35" in 2005, and received an NSF CAREER Award in 2004 and a Sloan Foundation Fellowship in 2007. He has also received best paper awards in VLDB 2004 and 2007 and in MobiCom 2006. In addition, he was recognized with a test of time award in SIGMOD 2013 for his work on acquisitional query processing, a 10-year best paper award in VLDB 2015 for his work on the C-Store system, a test-of time award in SIGMOD 2017 for his work on the Borealis stream processor, and a 2019 test of time award for his work on the VTrack system in SenSys. He was a co-founder of Vertica Systems, acquired by HP in 2012, and a founder of Cambridge Mobile Telematics, a leading vendor of smartphone-based technologies for make roads safer by making drivers better.
第37届CCF中国数据库学术会议（NDBC 2020）
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