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» Learning Models for Object Recognition
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137
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MVA
2010
130views Computer Vision» more  MVA 2010»
15 years 1 months ago
Neighborhood linear embedding for intrinsic structure discovery
In this paper, an unsupervised learning algorithm, neighborhood linear embedding (NLE), is proposed to discover the intrinsic structures such as neighborhood relationships, global ...
Shuzhi Sam Ge, Feng Guan, Yaozhang Pan, Ai Poh Loh
NIPS
2001
15 years 4 months ago
The Steering Approach for Multi-Criteria Reinforcement Learning
We consider the problem of learning to attain multiple goals in a dynamic environment, which is initially unknown. In addition, the environment may contain arbitrarily varying ele...
Shie Mannor, Nahum Shimkin
293
Voted

Book
5396views
17 years 2 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
ICCV
2005
IEEE
16 years 5 months ago
Identifying Individuals in Video by Combining "Generative" and Discriminative Head Models
The objective of this work is automatic detection and identification of individuals in unconstrained consumer video, given a minimal number of labelled faces as training data. Whi...
Mark Everingham, Andrew Zisserman
145
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AUTOID
2005
IEEE
15 years 9 months ago
Statistical Models for Assessing the Individuality of Fingerprints
Following Daubert in 1993, forensic evidence based on fingerprints was first challenged in the 1999 case of USA vs. Byron Mitchell, and subsequently, in 20 other cases involving...
Sarat C. Dass, Yongfang Zhu, Anil K. Jain