This paper proposes a framework to aid video analysts in detecting suspicious activity within the tremendous amounts of video data that exists in today’s world of omnipresent su...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
We study a novel shallow information extraction problem that involves extracting sentences of a given set of topic categories from medical forum data. Given a corpus of medical fo...
An automatic computer-aided detection system is developed for detecting pulmonary nodules from high resolution CT data. The system is based on the concept of machine learning. A ro...
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...