Deep Networks and Beyond: Vision and Machine Learning
- 작성자관리자
- 배포일2018.07.10
- 조회수291
ㅇ 제목 : Deep Networks and Beyond: Vision and Machine Learning
ㅇ 일시 : 2018년 7월 13일 금요일 16:00 ~
ㅇ 장소 : ETRI 7동 국제회의실
ㅇ 강사 : 알란 율 교수님 Prof. Alan L. Yuille (Bloomberg Distinguished Professor)
ㅇ 요약:
Deep networks are very successful for computer vision applications provided there are large annotated datasets enabling supervised learning and testing. But there remain important challenges. Firstly, "unrepresentative datasets", where the deep networks are sensitive to adversarial attacks, changes in context, and to rare or hazardous events. Secondly, "limited supervised training data" which requires transfer learning to deal with few training examples and weak supervision. Finally, "architecture design", where the goal is to automatically search over deep network architectures or to couple deep networks with other machine learning techniques such as random forests. This talk will address all these issues using state of the art computer vision applications.
