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» Making inferences with small numbers of training sets
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NECO
2007
127views more  NECO 2007»
13 years 4 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado
MM
2005
ACM
172views Multimedia» more  MM 2005»
13 years 10 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
CVPR
2008
IEEE
14 years 6 months ago
Sparse probabilistic regression for activity-independent human pose inference
Discriminative approaches to human pose inference involve mapping visual observations to articulated body configurations. Current probabilistic approaches to learn this mapping ha...
Raquel Urtasun, Trevor Darrell
ICPR
2000
IEEE
14 years 5 months ago
Face Reconstruction from a Small Number of Feature Points
This paper proposes a method for face reconstruction that makes use of only a small set of feature points. Faces can be modeled by forming linear combinations of prototypes of sha...
Bon-Woo Hwang, Seong-Whan Lee, Volker Blanz, Thoma...
MICCAI
2000
Springer
13 years 8 months ago
Small Sample Size Learning for Shape Analysis of Anatomical Structures
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...