Machine Learning, Deep Learning and AI in Consumer Electronics (CE) - Let′s talk about CES and ICCE in Las Vegas

Mission and Objective

The mission and objective of the IEEE CTSoc Machine learning, Deep learning and AI in CE (MDA) Technical Committee (TC) is to support the IEEE CTSoc activities with respect to machine learning (including deep learning) for embedded devices with power and computing constraints. The MDA TC is a cluster of engineers, practitioners, technologists, scientists, and researchers from Industry and Academia from around the world with the focus on attracting high-quality paper and journal submissions with respect to edge-computing-related machine learning and establishing a well-renowned technical stream and conference track.

The committee assumes the proactive duty to recommend suitable candidates from MDA TC members to serve as:

• Chairs and or Members of Technical Program Committees (TPC) of CTSoc Conferences (ICCE-Las Vegas, ICCE-Berlin, ICCE-Taiwan, ICCE-Asia, GCCEJapan, ISCT, and GEM).
• EiCs, Associates Editors and Editors to CTSoc Publications (IEEE Transactions on Consumer Electronics, IEEE ACCESS Section for Consumer Technology Society (Open Access), IEEE Consumer Electronics Magazine, News on Consumer Technology-NCT, CTSoc World Newsletter).
• Distinguished Lecturers and tutorials for CTSoc Education.
• Members of CTSoc Standards Committees and Working Groups.

Session Chair Danilo Pietro Pau (STMicroelectronics S.r.l.) talks about Machine Learning, Deep Learning and AI in CE

Danilo, Politecnico di Milano, Monza und Brianza, Lombardy, ItalyTechnical Director, IEEE and ST Fellow https://www.dhirubhai.net/in/danilopietropau/ is one of the founders of the Consumer Technolgy Society (CTSoc) former Consumer Electronics Society (CE). He is Session Chair of the Session 1 Friday, January 6th, 01:30-03:00 PM (PST) "Machine Learning, Deep Learning and AI in CE (MDA)"

Live Interview

1570860057???????A Real-Time Reconfigurable AI Processor Based-On FPGA, Yue Ri Jeong, Kwonneung Cho, Youngwoo Jeong, Seung Eun Lee and Sun Beom Kwon (Seoul National University of Science and Technology, Korea (South))

1570859536???????Stereo Matching with Supplementary Boundary Information, Kaito Hashimoto and Masaaki Ikehara (Keio University, Japan)

1570859439???????Addressing Straggler Problem Through Dynamic Partial All-Reduce for Distributed Deep Learning in Heterogeneous GPU Clusters, HyungJun Kim, Chunggeon Song, HwaMin Lee and Heonchang Yu (Korea University, Korea (South))

1570860772???????D2D: Divide to Detect, A Scale-Aware Framework for On-Road Object Detection Using IR Camera, Van-Tin Luu and Vu-Hoang Tran (Ho Chi Minh City University of Technology and Education, Vietnam); Egor Poliakov and Ching-Chun Huang (National Yang Ming Chiao Tung University, Taiwan)