This paper proposes a content-based medical image retrieval (CBMIR) framework using dynamically optimized features from multiple regions of medical images. These regional features...
Wei Xiong, Bo Qiu, Qi Tian, Changsheng Xu, Sim Hen...
This paper investigates a class of learning problems called learning satisfiability (LSAT) problems, where the goal is to learn a set in the input (feature) space that satisfies...
Frederic Thouin, Mark Coates, Brian Eriksson, Robe...
—In this paper, we develop an opportunistic spectrum scheduling scheme for cognitive radio networks. In the proposed scheme, the channel status (i.e., whether being occupied by p...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Monitoring transit traffic at one or more points in a network is of interest to network operators for reasons of traffic accounting, debugging or troubleshooting, forensics, and tr...