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CVPR
2010
IEEE
16 years 1 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
ISLPED
2009
ACM
100views Hardware» more  ISLPED 2009»
16 years 20 days ago
Tuning-friendly body bias clustering for compensating random variability in subthreshold circuits
Post-fabrication tuning for mitigating manufacturing variability is receiving a significant attention. To reduce leakage increase involved in performance compensation by body bia...
Koichi Hamamoto, Masanori Hashimoto, Yukio Mitsuya...
ICCCN
2008
IEEE
16 years 18 days ago
Fair Randomized Antenna Allocation in Asynchronous MIMO Multi-Hop Networks
Abstract—Previous work has shown that CSMA-based protocols such as the IEEE 802.11 can yield flow starvation in multihop wireless networks. While prior protocol designs alleviat...
Ahmed Khattab, Ashutosh Sabharwal, Edward W. Knigh...
CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
15 years 10 months ago
A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...
Zoltan Kato, Ting-Chuen Pong
EMMCVPR
2001
Springer
15 years 10 months ago
A Hierarchical Markov Random Field Model for Figure-Ground Segregation
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Stella X. Yu, Tai Sing Lee, Takeo Kanade