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ECAI
2008
Springer
15 years 8 months ago
Learning Functional Object-Categories from a Relational Spatio-Temporal Representation
Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
ICPR
2002
IEEE
16 years 7 months ago
Learning and Extracting Edges from Images by a Modified Hopfield Neural Network
This paper introduced a modified unsupervised Hopfield network that can learn the underlying process in an edge detection task from grey level images. After the learning phase, th...
Sylvain Chartier, Richard Lepage
165
Voted
PAMI
2008
139views more  PAMI 2008»
15 years 6 months ago
A Fast Algorithm for Learning a Ranking Function from Large-Scale Data Sets
We consider the problem of learning a ranking function that maximizes a generalization of the Wilcoxon-Mann-Whitney statistic on the training data. Relying on an -accurate approxim...
Vikas C. Raykar, Ramani Duraiswami, Balaji Krishna...
JMLR
2010
103views more  JMLR 2010»
15 years 1 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
CVPR
2006
IEEE
16 years 8 months ago
Learning Object Shape: From Drawings to Images
We consider the important challenge of recognizing a variety of deformable object classes in images. Of fundamental importance and particular difficulty in this setting is the pro...
Gal Elidan, Geremy Heitz, Daphne Koller