Intrusion detection systems (IDSs) attempt to identify attacks by comparing collected data to predefined signatures known to be malicious (misuse-based IDSs) or to a model of lega...
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
— Despite their popularity, occupancy grids cannot be directly applied to problems where the identity of the objects populating an environment needs to be taken into account (eg ...
Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...