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CVPR
2008
IEEE
16 years 8 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 2 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
SOCC
2008
IEEE
124views Education» more  SOCC 2008»
16 years 1 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
GLVLSI
2007
IEEE
140views VLSI» more  GLVLSI 2007»
16 years 1 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 8 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