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» Visual Object Recognition Through One-Class Learning
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ICCV
2005
IEEE
16 years 1 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
CVPR
2010
IEEE
15 years 8 months ago
Learning Mid-Level Features For Recognition
Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer representations of interme...
Y-Lan Boureau, Francis Bach, Yann LeCun, Jean Ponc...
ICCV
2001
IEEE
16 years 1 months ago
Learning the Semantics of Words and Pictures
We present a statistical model for organizing image collections which integrates semantic information provided by associated text and visual information provided by image features...
Kobus Barnard, David A. Forsyth
ICCV
2007
IEEE
16 years 1 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...
AGI
2011
14 years 3 months ago
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
Human intelligence consists largely of the ability to recognize and exploit structural systematicity in the world, relating our senses simultaneously to each other and to our cogni...
Derek Monner, James A. Reggia