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IJCV
2008
192views more  IJCV 2008»
13 years 9 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
BC
2005
127views more  BC 2005»
13 years 9 months ago
Computational modeling and exploration of contour integration for visual saliency
Abstract Weproposeacomputationalmodelofcontourintegration for visual saliency. The model uses biologically plausible devices to simulate how the representations of elements aligned...
T. Nathan Mundhenk, Laurent Itti
IBPRIA
2007
Springer
14 years 3 months ago
False Positive Reduction in Breast Mass Detection Using Two-Dimensional PCA
In this paper we present a novel method for reducing false positives in breast mass detection. Our approach is based on using the Two-Dimensional Principal Component Analysis (2DPC...
Arnau Oliver, Xavier Lladó, Joan Mart&iacut...
PR
2007
325views more  PR 2007»
13 years 8 months ago
Fingerprint enhancement using STFT analysis
Contrary to popular belief, despite decades of research in fingerprints, reliable fingerprint recognition is still an open problem. Extracting features out of poor quality print...
Sharat Chikkerur, Alexander N. Cartwright, Venu Go...
IJCV
2007
196views more  IJCV 2007»
13 years 9 months ago
Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning...
Robert Fergus, Pietro Perona, Andrew Zisserman