We investigate the problem of learning optimal descriptors for a given classification task. Many hand-crafted descriptors have been proposed in the literature for measuring visua...
K-means is a widely used partitional clustering method. A large amount of effort has been made on finding better proximity (distance) functions for K-means. However, the common c...
—In this paper, we present a positioning and tracking scheme based on adaptive weighted interpolation and Kalman filtering for wireless sensor networks. The proposed positioning ...
A new mutation concept is proposed to generalize local selection based Differential Evolution algorithm to work in general multimodal problems. Three variations of the proposed me...
In this paper, we present two linear-size external memory data structures for approximate range searching. Our first structure, the BAR-B-tree, stores a set of N points in Rd and ...