This paper describes an approach for using several levels of data fusion in the domain of autonomous off-road navigation. We are focusing on outdoor obstacle detection, and we pre...
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
In this paper, we try to develop a machine learning-based virus email detection method. The key feature of this paper is employing Mail Header and Encoding Anomaly(MHEA) [1]. MHEA ...
The system presented in this paper finds images and line-drawings in scanned pages; it is a crucial processing step in the creation of a large-scale system to detect and index ima...
— The basic objective of this work is to assess the utility of two supervised learning algorithms AdaBoost and RIPPER for classifying SSH traffic from log files without using f...