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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
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BEGIN:VEVENT
DTSTAMP:20221025T200451Z
UID:29A17DBE-53CA-46D0-B0CD-0A6A9C781229
DTSTART;TZID=Asia/Kolkata:20221019T190000
DTEND;TZID=Asia/Kolkata:20221019T195900
DESCRIPTION:Medical Image Segmentation is a challenging area of research wh
 ere Deep Learning algorithms have shown lot of success in recent times.\n\
 nIn this talk\, we would get an introduction to Deep Learning based segmen
 tation of Medical images. A brief overview of UNets would be covered to in
 troduce the audience to segmentation architectures.The second part of the 
 talk would be on Attention mechanism. Attention mechanism has revolutioniz
 ed Deep Learning algorithms\, especially in NLP domain and more recently i
 n Computer Vision tasks.In this talk\, after a brief introduction to atten
 tion blocks (from NLP context) we start with some of the attention approac
 hesor computer vision tasks. We dive in more detail on couple of attention
  blocks – criss-cross attention and attention-augmented-convolution.Some
  of the active frontiers in attention blocks (deformable attention) would 
 be finally discussed to give some insights on current research directions.
 \n\nSpeaker(s): Dr.Kumar Rajamani\, \n\nVirtual: https://events.vtools.iee
 e.org/m/328090
LOCATION:Virtual: https://events.vtools.ieee.org/m/328090
ORGANIZER:kundammrao@gmail.com
SEQUENCE:2
SUMMARY:Medical Image Segmentation using Deep Learning approaches (Transfor
 mers in Medical Segmentation
URL;VALUE=URI:https://events.vtools.ieee.org/m/328090
X-ALT-DESC:Description: <br /><p>Medical Image Segmentation is a challengin
 g area of research where Deep Learning algorithms have shown lot of succes
 s in recent times.</p>\n<p>In this talk\, we would get an introduction to 
 Deep Learning based segmentation of Medical images. A brief overview of UN
 ets would be covered to introduce the audience to segmentation architectur
 es.The second part of the talk would be on Attention mechanism.&nbsp\; Att
 ention mechanism has revolutionized Deep Learning algorithms\, especially 
 in NLP domain and more recently in Computer Vision tasks.In this talk\, af
 ter a brief introduction to attention blocks (from NLP context) we start w
 ith some of the attention approachesor computer vision tasks. We dive in m
 ore detail on couple of attention blocks &ndash\; criss-cross attention an
 d attention-augmented-convolution.Some of the active frontiers in attentio
 n blocks (deformable attention) would be finally discussed to give some in
 sights on current research directions.</p>\n<p>&nbsp\;</p>
END:VEVENT
END:VCALENDAR