We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
This paper proposes a novel approach to segment three dimensional curvilinear structures, particularly vessels in angiography, by inspecting the symmetry of image gradients. The pr...
Constrained gradient analysis (similar to the “cubegrade” problem posed by Imielinski, et al. [9]) is to extract pairs of similar cell characteristics associated with big chan...
Guozhu Dong, Jiawei Han, Joyce M. W. Lam, Jian Pei...
This paper presents a reliable coin recognition system that is based on a registration approach. To optimally align two coins we search for a rotation in order to reach a maximal n...
We introduce an Augmented Histograms of Oriented Gradients (AHOG) feature for human detection from a nonstatic camera. We increase the discriminating power of original Histograms ...
—Evolutionary gradient search is a hybrid algorithm that exploits the complementary features of gradient search and evolutionary algorithm to achieve a level of efficiency and r...
Chi Keong Goh, Yew-Soon Ong, Kay Chen Tan, Eu Jin ...
—This paper reviews the different gradient-based schemes and the sources of gradient, their availability, precision and computational complexity, and explores the benefits of usi...
Boyang Li, Yew-Soon Ong, Minh Nghia Le, Chi Keong ...
Abstract. Gradients are distributed distance estimates used as a building block in many sensor network applications. In large or long-lived deployments, it is important for the est...
Jacob Beal, Jonathan Bachrach, Daniel Vickery, Mar...
Abstract— The role of gradient estimation in global optimization is investigated. The concept of a regional gradient is introduced as a tool for analyzing and comparing different...