BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Asia/Kolkata
BEGIN:STANDARD
DTSTART:19451014T230000
TZOFFSETFROM:+0630
TZOFFSETTO:+0530
TZNAME:IST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20250818T172708Z
UID:F2E9BE1A-8423-4E56-8CDD-AD110E45A826
DTSTART;TZID=Asia/Kolkata:20250812T090000
DTEND;TZID=Asia/Kolkata:20250812T120000
DESCRIPTION:Video analytics is undergoing a revolutionary shift with the in
 tegration of Artificial Intelligence at the Edge. Traditional centralized 
 processing struggles to meet the demands of real-time decision-making\, lo
 w latency\, and high data volumes generated by modern video systems. The t
 echnical talk on “Intelligent Vision: Redefining Video Analytics with AI
  at the Edge” explored how edge-based AI models are enabling smarter\, f
 aster\, and more efficient video analysis closer to the data source.\n\nSp
 eaker(s): \, SUPAVADEE\n\nChennai\, Tamil Nadu\, India
LOCATION:Chennai\, Tamil Nadu\, India
ORGANIZER:sku-maheswaran@ieee.org
SEQUENCE:10
SUMMARY:Technical Talk on "Intelligent Vision: Redefining Video Analytics w
 ith AI at the Edge
URL;VALUE=URI:https://events.vtools.ieee.org/m/497283
X-ALT-DESC:Description: <br /><p>Video analytics is undergoing a revolution
 ary shift with the integration of <strong data-start="343" data-end="382">
 Artificial Intelligence at the Edge</strong>. Traditional centralized proc
 essing struggles to meet the demands of <strong data-start="452" data-end=
 "517">real-time decision-making\, low latency\, and high data volumes</str
 ong> generated by modern video systems. The technical talk on <em data-sta
 rt="576" data-end="646">&ldquo\;Intelligent Vision: Redefining Video Analy
 tics with AI at the Edge&rdquo\;</em> explored how <strong data-start="664
 " data-end="688">edge-based AI models</strong> are enabling smarter\, fast
 er\, and more efficient video analysis closer to the data source.</p>
END:VEVENT
END:VCALENDAR