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NIPS
2004
13 years 8 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
STACS
2000
Springer
13 years 11 months ago
On the Many Faces of Block Codes
Abstract. Block codes are first viewed as finite state automata represented as trellises. A technique termed subtrellis overlaying is introduced with the object of reducing decoder...
Kaustubh Deshmukh, Priti Shankar, Amitava Dasgupta...
PAMI
2010
190views more  PAMI 2010»
13 years 5 months ago
OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues
—We present a probabilistic method for segmenting instances of a particular object category within an image. Our approach overcomes the deficiencies of previous segmentation tech...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
14 years 7 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
ECCV
2008
Springer
14 years 9 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal