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CVPR
2008
IEEE
16 years 6 months ago
Combining appearance models and Markov Random Fields for category level object segmentation
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
Diane Larlus, Frédéric Jurie
CVPR
2010
IEEE
16 years 4 days 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
SOCC
2008
IEEE
124views Education» more  SOCC 2008»
15 years 11 months ago
Energy minimization using a greedy randomized heuristic for the voltage assignment problem in NoC
— Scaling down the voltage levels of the processing elements (PEs) in a Network-on-Chip (NoC) can significantly reduce the computation energy consumption with an overhead of the...
Pavel Ghosh, Arunabha Sen
133
Voted
GLVLSI
2007
IEEE
140views VLSI» more  GLVLSI 2007»
15 years 11 months ago
Structured and tuned array generation (STAG) for high-performance random logic
Regularly structured design techniques can combat complexity on a variety of fronts. We present the Structured and Tuned Array Generation (STAG) design methodology, which provides...
Matthew M. Ziegler, Gary S. Ditlow, Stephen V. Kos...
IJCAI
2007
15 years 6 months ago
Recursive Random Fields
A formula in first-order logic can be viewed as a tree, with a logical connective at each node, and a knowledge base can be viewed as a tree whose root is a conjunction. Markov l...
Daniel Lowd, Pedro Domingos