We present a new pedestrian detector that improves both in speed and quality over state-of-the-art. By efficiently handling different scales and transferring computation from tes...
Rodrigo Benenson, Markus Mathias, Radu Timofte, Lu...
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
Detecting local clustered anomalies is an intricate problem for many existing anomaly detection methods. Distance-based and density-based methods are inherently restricted by their...
— The ad-hoc methodology that is prevalent in today’s testing and evaluation of network intrusion detection algorithms and systems makes it difficult to compare different algor...
Nicholas Athanasiades, Randal Abler, John G. Levin...
We proposed a new foreground detection method using the static cameras. It merges multi-modality into graph cut energy function, and performs much better results than conventional...