This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
Learning to cope with domain change has been known
as a challenging problem in many real-world applications.
This paper proposes a novel and efficient approach, named
domain ada...
Yu-Gang Jiang, Jun Wang, Shih-Fu Chang, Chong-Wah ...
This paper presents a cooperative evolutionary approach for the problem of instance selection for instance based learning. The presented model takes advantage of one of the most r...
Abstract. One of the main problems associated with arti cial neural networks online learning methods is the estimation of model order. In this paper, we report about a new approach...
This paper describes an online learning based method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. Our fire detection method...