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CBMS
2006
IEEE
16 years 16 days ago
Machine Learning Techniques to Enable Closed-Loop Control in Anesthesia
The growing availability of high throughput measurement devices in the operating room makes possible the collection of a huge amount of data about the state of the patient and the...
Olivier Caelen, Gianluca Bontempi, Eddy Coussaert,...
ICIP
2009
IEEE
15 years 4 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
CN
1999
116views more  CN 1999»
15 years 6 months ago
Network-conscious GIF image transmission over the Internet
Traditional image compression techniques seek the smallest possible le size for a given level of image quality. By contrast, network-conscious image compression techniques take in...
Paul D. Amer, Sami Iren, Gul E. Sezen, Phillip T. ...
ISVC
2010
Springer
15 years 5 months ago
Attention-Based Target Localization Using Multiple Instance Learning
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
Karthik Sankaranarayanan, James W. Davis
ECCV
2008
Springer
16 years 8 months ago
Learning for Optical Flow Using Stochastic Optimization
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
Yunpeng Li, Daniel P. Huttenlocher