In this paper, we introduce a novel framework for clustering web data which is often heterogeneous in nature. As most existing methods often integrate heterogeneous data into a un...
Identifying intrinsic structures in large networks is a fundamental problem in many fields, such as engineering, social science and biology. In this paper, we are concerned with c...
We present a new framework for data hiding in images printed with clustered dot halftones. Our application scenario, like other hardcopy embedding methods, encounters fundamental c...
This paper describes a new method for analysis/synthesis of textures using a non-parametric multi-resolution approach able to reproduce efficiently the generative stochastic proce...
Sebastiano Battiato, Alfredo Pulvirenti, Diego Ref...
Background: Gene clustering for annotating gene functions is one of the fundamental issues in bioinformatics. The best clustering solution is often regularized by multiple constra...
Jia Zeng, Shanfeng Zhu, Alan Wee-Chung Liew, Hong ...