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17 years 5 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
CVPR
2009
IEEE
17 years 1 months ago
Global Connectivity Potentials for Random Field Models
Markov random field (MRF, CRF) models are popular in computer vision. However, in order to be computationally tractable they are limited to incorporate only local interactions a...
Sebastian Nowozin, Christoph H. Lampert
ICCV
2009
IEEE
16 years 11 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
DAC
2003
ACM
16 years 7 months ago
Random walks in a supply network
This paper presents a power grid analyzer based on a random walk technique. A linear-time algorithm is first demonstrated for DC analysis, and is then extended to perform transien...
Haifeng Qian, Sani R. Nassif, Sachin S. Sapatnekar
ASPLOS
2010
ACM
16 years 1 months ago
A randomized scheduler with probabilistic guarantees of finding bugs
This paper presents a randomized scheduler for finding concurrency bugs. Like current stress-testing methods, it repeatedly runs a given test program with supplied inputs. Howeve...
Sebastian Burckhardt, Pravesh Kothari, Madanlal Mu...