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CVPR
2008
IEEE
16 years 9 months ago
Mining compositional features for boosting
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
Junsong Yuan, Jiebo Luo, Ying Wu
ICCV
2003
IEEE
16 years 9 months ago
Ranking Prior Likelihood Distributions for Bayesian Shape Localization Framework
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
Shuicheng Yan, Mingjing Li, HongJiang Zhang, QianS...
BROADNETS
2004
IEEE
15 years 11 months ago
Random Asynchronous Wakeup Protocol for Sensor Networks
This paper presents Random Asynchronous Wakeup (RAW), a power saving technique for sensor networks that reduces energy consumption without significantly affecting the latency or c...
Vamsi Paruchuri, Shivakumar Basavaraju, Arjan Durr...
NIPS
2008
15 years 9 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
BMCBI
2008
211views more  BMCBI 2008»
15 years 7 months ago
CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment
Background: Searching for similarities in protein and DNA databases has become a routine procedure in Molecular Biology. The Smith-Waterman algorithm has been available for more t...
Svetlin Manavski, Giorgio Valle