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» A reinforcement learning model of selective visual attention
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MM
2005
ACM
99views Multimedia» more  MM 2005»
14 years 1 months ago
To learn representativeness of video frames
With the rapid explosion of video data, compact representation of videos is becoming more and more desirable for efficient browsing and communication, which leads to a number of r...
Hong-Wen Kang, Xian-Sheng Hua
IJCV
2008
192views more  IJCV 2008»
13 years 7 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
ITS
2000
Springer
94views Multimedia» more  ITS 2000»
13 years 11 months ago
DT Tutor: A Decision-Theoretic, Dynamic Approach for Optimal Selection of Tutorial Actions
DT Tutor uses a decision-theoretic approach to select tutorial actions for coached problem solving that are optimal given the tutor's beliefs and objectives. It employs a mode...
R. Charles Murray, Kurt VanLehn
ICCV
2011
IEEE
12 years 7 months ago
Annotator Rationales for Visual Recognition
Traditional supervised visual learning simply asks annotators “what” label an image should have. We propose an approach for image classification problems requiring subjective...
Jeff Donahue, Kristen Grauman
UM
2010
Springer
13 years 5 months ago
Inducing Effective Pedagogical Strategies Using Learning Context Features
Effective pedagogical strategies are important for e-learning environments. While it is assumed that an effective learning environment should craft and adapt its actions to the use...
Min Chi, Kurt VanLehn, Diane J. Litman, Pamela W. ...