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106
Voted
ICDM
2008
IEEE
126views Data Mining» more  ICDM 2008»
15 years 11 months ago
Detecting Suspicious Behavior in Surveillance Images
We introduce a novel technique to detect anomalies in images. The notion of normalcy is given by a baseline of images, under the assumption that the majority of such images is nor...
Daniel Barbará, Carlotta Domeniconi, Zoran ...
ICDCSW
2011
IEEE
14 years 4 months ago
Finding a "Kneedle" in a Haystack: Detecting Knee Points in System Behavior
—Computer systems often reach a point at which the relative cost to increase some tunable parameter is no longer worth the corresponding performance benefit. These “knees” t...
Ville Satopaa, Jeannie R. Albrecht, David Irwin, B...
CRV
2005
IEEE
191views Robotics» more  CRV 2005»
15 years 10 months ago
Automated Behavioral Phenotype Detection and Analysis Using Color-Based Motion Tracking
The problem of elucidating the functional significance of genes is a key challenge of modern science. Solving this problem can lead to fundamental advancements across multiple are...
Alan Shimoide, Ilmi Yoon, Megumi Fuse, Holly C. Be...
CIDM
2007
IEEE
15 years 4 months ago
Detection of Unknown Computer Worms Activity Based on Computer Behavior using Data Mining
— Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, aft...
Robert Moskovitch, Ido Gus, Shay Pluderman, Dima S...
105
Voted
CHI
2009
ACM
15 years 11 months ago
Tracking behavior in persuasive apps: is sensor-based detection always better than user self-reporting?
This paper aims to discuss the roles for the two types of tracking user behavior. Considering these two types of tracking, sensor based recognition has a great advantage when sens...
Miyuki Shiraishi, Yasuyuki Washio, Chihiro Takayam...