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» Learning Models for Object Recognition
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FLAIRS
2010
15 years 5 months ago
Learning to Identify and Track Imaginary Objects Implied by Gestures
A vision-based machine learner is presented that learns characteristic hand and object movement patterns for using certain objects, and uses this information to recreate the "...
Andreya Piplica, Alexandra Olivier, Allison Petros...
CVPR
2012
IEEE
13 years 5 months ago
Adaptive object tracking by learning background context
One challenge when tracking objects is to adapt the object representation depending on the scene context to account for changes in illumination, coloring, scaling, etc. Here, we p...
Ali Borji, Simone Frintrop, Dicky N. Sihite, Laure...
AVSS
2006
IEEE
15 years 9 months ago
The Role of Motion Models in Super-Resolving Surveillance Video for Face Recognition
Although the use of super-resolution techniques has demonstrated the ability to improve face recognition accuracy when compared to traditional upsampling techniques, they are difï...
Frank Lin, Clinton Fookes, Vinod Chandran, Sridha ...
CVPR
2006
IEEE
16 years 5 months ago
Supervised Learning of Edges and Object Boundaries
Edge detection is one of the most studied problems in computer vision, yet it remains a very challenging task. It is difficult since often the decision for an edge cannot be made ...
Piotr Dollár, Zhuowen Tu, Serge Belongie
NPL
2002
117views more  NPL 2002»
15 years 2 months ago
Invariant Recognition of Spatio Temporal Patterns in The Olfactory System Model
This paper presents a model of a network of integrate-and-fire neurons with time delay weights, capable of invariant spatio-temporal pattern recognition. Spatio-temporal patterns a...
Mykola Lysetskiy, Andrzej Lozowski, Jacek M. Zurad...