BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Drupal iCal API//EN
X-WR-CALNAME:Events items teaser
X-WR-TIMEZONE:America/Toronto
BEGIN:VTIMEZONE
TZID:America/Toronto
X-LIC-LOCATION:America/Toronto
BEGIN:DAYLIGHT
TZNAME:EDT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
DTSTART:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZNAME:EST
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
DTSTART:20191103T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
UID:69b62939b42c9
DTSTART;TZID=America/Toronto:20200120T090000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20200120T090000
URL:https://uwaterloo.ca/artificial-intelligence-group/events/masters-thesi
 s-presentation-accelerating-training
LOCATION:E7 - Engineering 7 200 University Ave West 5417 Waterloo ON N2L 3G
 1 Canada
SUMMARY:Master’s Thesis Presentation: Accelerating the Training of\nConvo
 lutional Neural Networks for Image Segmentation with Deep Active\nLearning
CLASS:PUBLIC
DESCRIPTION:WEI TAO CHEN\, MASTER’S CANDIDATE\n_David R. Cheriton School 
 of Computer Science_\n\nImage semantic segmentation is an important proble
 m in computer\nvision. However\, training a deep neural network for semant
 ic\nsegmentation in supervised learning requires expensive manual\nlabelin
 g. Active learning (AL) addresses this problem by automatically\nselecting
  a subset of the dataset to label and iteratively improve the\nmodel. This
  minimizes labeling costs while maximizing performance.\nYet\, deep active
  learning for image segmentation has not been\nsystematically studied in t
 he literature. 
DTSTAMP:20260315T033625Z
END:VEVENT
END:VCALENDAR