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:20230821T045703Z UID:E770F63B-56B2-4589-98E8-E292D7C8DD60 DTSTART;TZID=Asia/Kolkata:20230818T123000 DTEND;TZID=Asia/Kolkata:20230818T133000 DESCRIPTION:Human activity recognition with radar sensors has attracted a l ot of attention\, starting initially from fall detection and moving to the classification of more complex patterns of activities as well as hand ges tures and vital signs. While initial research in this domain considered ac tivities and human body movements as artificially separated\, individual ‘snapshot-like’ data\, more recent work explores techniques that can d eal with more realistic\, unconstrained sequences of continuous activities . This talk will briefly overview recently proposed research and radar-bas ed human activity recognition techniques\, focussing on the radar signal p rocessing tools and machine learning techniques proposed in the state-of-t he-art literature.\n\nSpeaker(s): Dr. Francesco Fioranelli\n\nVirtual: htt ps://events.vtools.ieee.org/m/369295 LOCATION:Virtual: https://events.vtools.ieee.org/m/369295 ORGANIZER:ieee.iitkgp.sb@gmail.com SEQUENCE:25 SUMMARY:IEEE Student Branch\, IIT Kharagpur presents an invited talk on “ Radar approaches for sequential human activity classification” URL;VALUE=URI:https://events.vtools.ieee.org/m/369295 X-ALT-DESC:Description: <br /><p>Human activity recognition with radar sens ors has attracted a lot of attention\, starting initially from fall detect ion and moving to the classification of more complex patterns of activitie s as well as hand gestures and vital signs. While initial research in this domain considered activities and human body movements as artificially sep arated\, individual &lsquo\;snapshot-like&rsquo\; data\, more recent work explores techniques that can deal with more realistic\, unconstrained sequ ences of continuous activities. This talk will briefly overview recently p roposed research and radar-based human activity recognition techniques\, f ocussing on the radar signal processing tools and machine learning techniq ues proposed in the state-of-the-art literature.</p>\n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR