BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Europe/London
BEGIN:DAYLIGHT
DTSTART:20260329T020000
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:BST
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20251026T010000
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:GMT
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20251123T160817Z
UID:BD004AEE-575F-479F-ACA2-03BC80DF391F
DTSTART;TZID=Europe/London:20251119T133000
DTEND;TZID=Europe/London:20251119T143000
DESCRIPTION:In this talk\, Dr. Ihsan will discuss recent advances in video-
 based human activity recognition\, focusing on two distinct contributions.
  The first introduces a probabilistic sampling method based on the Frobeni
 us norm that enhances efficiency while maintaining recognition accuracy. T
 he second presents Video-DPRP\, a differentially private framework that pr
 otects visual privacy while supporting reliable activity recognition. Toge
 ther\, these works demonstrate the importance of both performance-driven a
 nd privacy-aware approaches in advancing video understanding\, ultimately 
 enabling more practical and trustworthy video-based activity recognition s
 ystems.\n\nCo-sponsored by: Ulster University\n\nSpeaker(s): Ihsan\, \n\nV
 irtual: https://events.vtools.ieee.org/m/505622
LOCATION:Virtual: https://events.vtools.ieee.org/m/505622
ORGANIZER:h.zheng@ulster.ac.uk
SEQUENCE:9
SUMMARY:Advances in Video Human Activity Recognition: Efficient Sampling an
 d Privacy Preservation
URL;VALUE=URI:https://events.vtools.ieee.org/m/505622
X-ALT-DESC:Description: <br /><p style="text-align: justify\;"><span style=
 "color: rgb(51\, 51\, 51)\; font-family: Garamond\, Helvetica\, serif\; fo
 nt-size: 18.75px\; font-style: normal\; font-variant-ligatures: normal\; f
 ont-variant-caps: normal\; font-weight: 300\; letter-spacing: normal\; orp
 hans: 2\; text-align: start\; text-indent: 0px\; text-transform: none\; wi
 dows: 2\; word-spacing: 0px\; -webkit-text-stroke-width: 0px\; white-space
 : normal\; text-decoration-thickness: initial\; text-decoration-style: ini
 tial\; text-decoration-color: initial\; display: inline !important\; float
 : none\;">In this talk\, Dr. Ihsan will discuss recent advances in video-b
 ased human activity recognition\, focusing on two distinct contributions. 
 The first introduces a probabilistic sampling method based on the Frobeniu
 s norm that enhances efficiency while maintaining recognition accuracy. Th
 e second presents Video-DPRP\, a differentially private framework that pro
 tects visual privacy while supporting reliable activity recognition. Toget
 her\, these works demonstrate the importance of both performance-driven an
 d privacy-aware approaches in advancing video understanding\, ultimately e
 nabling more practical and trustworthy video-based activity recognition sy
 stems.</span></p>
END:VEVENT
END:VCALENDAR