One of the primary issues with traditional anomaly detection approaches is their inability to handle complex, structural data. One approach to this issue involves the detection of...
The frequency and severity of a number of recent intrusions involving data theft and leakages has shown that online users’ trust, voluntary or not, in the ability of third partie...
The accurate quantification of disease patterns in medical images allows radiologists to track the progress of a disease. Various computer vision techniques are able to automatica...
Detecting bursts in data streams is an important and challenging task, especially in stock market, traffic control or sensor network streams. Burst detection means the identificat...
One of the biggest obstacles faced by user command based anomaly detection techniques is the paucity of data. Gathering command data is a slow process often spanning months or yea...