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UAI
1996
13 years 9 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
JAISE
2011
179views more  JAISE 2011»
12 years 10 months ago
A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera
Person tracking is an important topic in ambient living systems as well as in computer vision. In particular, detecting a person from a ceiling-mounted camera is a challenge since ...
Wenjie Yan, Cornelius Weber, Stefan Wermter
CCS
2007
ACM
14 years 1 months ago
Non-intrusive IP traceback for DDoS attacks
The paper describes a Non-Intrusive IP traceback scheme which uses sampled traffic under non-attack conditions to build and maintains caches of the valid source addresses transiti...
Vrizlynn L. L. Thing, Morris Sloman, Naranker Dula...
ISMAR
2003
IEEE
14 years 29 days ago
Fully Automated and Stable Registration for Augmented Reality Applications
We present a fully automated approach to camera registration for Augmented Reality systems. It relies on purely passive vision techniques to solve the initialization and realtime ...
Vincent Lepetit, Luca Vacchetti, Daniel Thalmann, ...
ECCV
2006
Springer
13 years 11 months ago
Motion Segmentation Using an Occlusion Detector
We present a novel method for the detection of motion boundaries in a video sequence based on differential properties of the spatio-temporal domain. Regarding the video sequence as...
Doron Feldman, Daphna Weinshall