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» Using stereo for object recognition
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ICCV
2009
IEEE
15 years 1 months ago
Incremental Multiple Kernel Learning for object recognition
A good training dataset, representative of the test images expected in a given application, is critical for ensuring good performance of a visual categorization system. Obtaining ...
Aniruddha Kembhavi, Behjat Siddiquie, Roland Miezi...
BC
2006
149views more  BC 2006»
15 years 3 months ago
Learning invariant object recognition in the visual system with continuous transformations
Abstract The cerebral cortex utilizes spatiotemporal continuity in the world to help build invariant representations. In vision, these might be representations of objects. The temp...
Simon M. Stringer, G. Perry, Edmund T. Rolls, J. H...
173
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ICIP
2009
IEEE
16 years 4 months ago
Pfid: Pittsburgh Fast-food Image Dataset
We introduce the first visual dataset of fast foods with a total of 4,545 still images, 606 stereo pairs, 303 3600 videos for structure from motion, and 27 privacy-preserving vide...
ICASSP
2010
IEEE
15 years 3 months ago
HMM-based pseudo-clean speech synthesis for splice algorithm
In this paper, we present a novel approach to relax the constraint of stereo-data which is needed in a series of algorithms for noise-robust speech recognition. As a demonstration...
Jun Du, Yu Hu, Li-Rong Dai, Ren-Hua Wang
COGSCI
2004
75views more  COGSCI 2004»
15 years 3 months ago
Object recognition and Random Image Structure Evolution
We present a technique called Random Image Structure Evolution (RISE) for use in experimental investigations of high-level visual perception. Potential applications of RISE includ...
Javid Sadr, Pawan Sinha