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PAMI
2002
108views more  PAMI 2002»
15 years 6 months ago
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC)
We propose a method for choosing the number of colors or true gray levels in an image; this allows fully automatic segmentation of images. Our underlying probability model is a hid...
Derek C. Stanford, Adrian E. Raftery
TCOM
2010
92views more  TCOM 2010»
15 years 4 months ago
Detection of Gaussian constellations in MIMO systems under imperfect CSI
Abstract—This paper considers the problem of Gaussian symbols detection in MIMO systems in the presence of channel estimation errors. Under this framework we develop a computatio...
Ido Nevat, Gareth W. Peters, Jinhong Yuan
TKDE
2010
150views more  TKDE 2010»
15 years 4 months ago
Prospective Infectious Disease Outbreak Detection Using Markov Switching Models
—Accurate and timely detection of infectious disease outbreaks provides valuable information which can enable public health officials to respond to major public health threats in...
Hsin-Min Lu, Daniel Zeng, Hsinchun Chen
CVPR
2011
IEEE
15 years 2 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
ICASSP
2011
IEEE
14 years 10 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...