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» Learning in Computer Vision: Some Thoughts
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ICVGIP
2004
13 years 8 months ago
On Learning Shapes from Shades
Shape from Shading (SFS) is one of the most extensively studied problems in Computer Vision. However, most of the approaches only deal with Lambertian or other specific shading mo...
Subhajit Sanyal, Mayank Bansal, Subhashis Banerjee...
IJCAI
1993
13 years 8 months ago
Evolutionary Learning Strategy using Bug-Based Search
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
DA
2010
123views more  DA 2010»
13 years 4 months ago
Paradoxes in Learning and the Marginal Value of Information
We consider the Bayesian ranking and selection problem, in which one wishes to allocate an information collection budget as efficiently as possible to choose the best among severa...
Peter Frazier, Warren B. Powell
ICCV
2007
IEEE
14 years 9 months ago
Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification
We address the problem of visual category recognition by learning an image-to-image distance function that attempts to satisfy the following property: the distance between images ...
Andrea Frome, Yoram Singer, Fei Sha, Jitendra Mali...
ECCV
2006
Springer
14 years 9 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...