Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
The usefulness of the hit-miss transform (HMT) and related transforms for pattern matching in document image applications is examined. Although the HMT is sensitive to the types o...
Covariance matrices have recently been a popular choice for versatile tasks like recognition and tracking due to their powerful properties as local descriptor and their low comput...
This paper is concerned with the development of a computational methodology based on fractal geometry for determining 3D structure of protein with imagery projection operations. I...
Abstract. Efficient nearest neighbor (NN) search techniques for highdimensional data are crucial to content-based image retrieval (CBIR). Traditional data structures (e.g., kd-tree...
Pengcheng Wu, Steven C. H. Hoi, Duc Dung Nguyen, Y...