— this paper presents a novel image feature extraction and recognition method two dimensional linear discriminant analysis (2DLDA) in a much smaller subspace. Image representatio...
R. M. Mutelo, Li Chin Khor, Wai Lok Woo, Satnam Si...
This paper presents a data-driven approach for feature selection to address the common problem of dealing with high-dimensional data. This approach is able to handle the real-valu...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
We present a new class of deformable models, MetaMorphs, whose formulation integrates both shape and interior texture. The model deformations are derived from both boundary and re...
Research in algorithms for Boolean satisfiability and their efficient implementations [26, 8] has recently outpaced benchmarking efforts. Most of the classic DIMACS benchmarks fro...
Fadi A. Aloul, Arathi Ramani, Igor L. Markov, Kare...