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DTSTAMP:20231130T220229Z
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DTSTART;TZID=America/Los_Angeles:20230929T163000
DTEND;TZID=America/Los_Angeles:20230929T183000
DESCRIPTION:Abstract: Both video compression and computer vision make use o
 f spatial and temporal patterns present in images. With the rise of the in
 ternet of video things\, numerous opportunities have arisen for synergizin
 g AI and video compression. In this presentation\, we will explore two mai
 n aspects. Firstly\, we'll delve into utilizing compressed data to perform
  AI tasks. Secondly\, we'll dive into harnessing AI for video compression 
 and image signal processing.\n\nBio: Dr. Yen-Kuang Chen received his Ph.D.
  degree from Princeton University. His research areas span from emerging a
 pplications that can utilize the true potential of multimedia and Internet
  of Things (IoT) to computer architecture that can embrace emerging applic
 ations. He has 100+ patents and 100+ technical publications. He is recogni
 zed as an IEEE Fellow for his contributions to algorithm-architecture co-d
 esign for multimedia signal processing.\n\nSpeaker(s): Yen-Kuang Chen\, \n
 \nRoom: 1301\, Bldg: SCDI\, Santa Clara University\, Santa Clara\, Califor
 nia\, United States
LOCATION:Room: 1301\, Bldg: SCDI\, Santa Clara University\, Santa Clara\, C
 alifornia\, United States
ORGANIZER:nandish@ieee.org
SEQUENCE:15
SUMMARY:The Synergy of AI and Video Compression in the Era of Internet of V
 ideo Things
URL;VALUE=URI:https://events.vtools.ieee.org/m/374979
X-ALT-DESC:Description: <br /><p>Abstract:&nbsp\;Both video compression and
  computer vision make use of spatial and temporal patterns present in imag
 es. With the rise of the internet of video things\, numerous opportunities
  have arisen for synergizing AI and video compression. In this presentatio
 n\, we will explore two main aspects. Firstly\, we'll delve into utilizing
  compressed data to perform AI tasks. Secondly\, we'll dive into harnessin
 g AI for video compression and image signal processing.&nbsp\;</p>\n<p>Bio
 : Dr. Yen-Kuang Chen received his Ph.D. degree from Princeton University. 
 His research areas span from emerging applications that can utilize the tr
 ue potential of multimedia and Internet of Things (IoT) to computer archit
 ecture that can embrace emerging applications. He has 100+ patents and 100
 + technical publications. He is recognized as an IEEE Fellow for his contr
 ibutions to algorithm-architecture co-design for multimedia signal process
 ing.</p>
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