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» Fine-grained object recognition in underwater visual data
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CVPR
2011
IEEE
12 years 12 months ago
Global Contrast based Salient Region Detection
Reliable estimation of visual saliency allows appropriate processing of images without prior knowledge of their content, and thus remains an important step in many computer vision ...
Ming-Ming Cheng, Guo-Xin Zhang, Niloy J. Mitra, Xi...
ECCV
2010
Springer
13 years 10 months ago
Robust Multi-View Boosting with Priors
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
IJSI
2008
156views more  IJSI 2008»
13 years 5 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
MM
2009
ACM
209views Multimedia» more  MM 2009»
13 years 12 months ago
Brain state decoding for rapid image retrieval
Human visual perception is able to recognize a wide range of targets under challenging conditions, but has limited throughput. Machine vision and automatic content analytics can p...
Jun Wang, Eric Pohlmeyer, Barbara Hanna, Yu-Gang J...
VLSISP
2010
254views more  VLSISP 2010»
13 years 3 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...