In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
—Anomaly detection is an important challenge for tasks such as fault diagnosis and intrusion detection in energy constrained wireless sensor networks. A key problem is how to min...
Sutharshan Rajasegarar, Christopher Leckie, Marimu...
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
This paper addresses the task of change analysis of correlated multi-sensor systems. The goal of change analysis is to compute the anomaly score of each sensor when we know that t...
Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challengin...
Yingyi Bu, Lei Chen 0002, Ada Wai-Chee Fu, Dawei L...