Abstract. Markov Random Fields (MRFs) 5] are a class of probabalistic models that have been applied for many years to the analysis of visual patterns or textures. In this paper, ou...
Deryck F. Brown, A. Beatriz Garmendia-Doval, John ...
Low-dimensional representations of sensory signals are key to solving many of the computational problems encountered in high-level vision. Principal Component Analysis (PCA) has b...
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
Static program checking tools can find many serious bugs in software, but due to analysis limitations they also frequently emit false error reports. Such false positives can easi...
Ted Kremenek, Ken Ashcraft, Junfeng Yang, Dawson R...
Copyright 2004 IEEE. Published in Conference on Computer Vision and Pattern Recognition (CVPR-2004), June 27 - July 2, 2004, Washington DC. Personal use of this material is permit...