Active Bibliography

1 Indoor Ad Hoc Proximity-Location Sensing for Service Provider Selection – Victor Azondekon, Michel Barbeau - 2003
Resident and Caregiver: Handling Multiple People in a Smart Care Facility – Aaron S. Cr, Diane J. Cook
1 Secure Distance-based Localization in the Presence of Cheating Beacon Nodes – Murtuza Jadliwala, Sheng Zhong, Shambhu Upadhyaya, Chunming Qiao, Senior Member, Jean-pierre Hubaux
48 Particle filters for location estimation in ubiquitous computing: A case study – Jeffrey Hightower, Gaetano Borriello - 2004
Semantic Multimedia: Mining, Fusion and Extraction PhD Work Plan – João Miguel, Costa Magalhães
Thesis in a Box – Mark Andrew Paskin, Mark Andrew, Mark Andrew Paskin - 2003
DIAGNOSIS METHOD FOR SPACECRAFT USING DYNAMIC BAYESIAN NETWORKS ABSTRACT – Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida
BayesTools: an Open-source Toolbox for Bayesian Modelling of Dynamic Systems – Vaclav Smidl
BAYESIAN DIAGNOSIS AND PROGNOSIS USING INSTRUMENT UNCERTAINTY – Phd Mark, A. Kaufman
Multi-rate Coupled Hidden Markov Models and Their Application to Machining Tool-Wear Classification – Özgür Çetin, Mari Ostendorf, Gary D. Bernard
A Hierarchical Graphical Model for Recognizing Human Actions and Interactions in Video – Sangho Park - 2004
A general framework for comparing (approximate) inference algorithms – Frank Hutter, Sohrab Shah
Contextual Computer Support for Human Activity – Donald Patterson And, Donald J. Patterson, Dieter Fox, Henry Kautz, Kenneth Fishkin, Mike Perkowitz, Matthai Philipose - 2004
Proposed design for gR, a graphical models toolkit for R – Kevin P. Murphy - 2003
Bayesian Techniques for Location Estimation – Dieter Fox Jeffrey, Jeffrey Hightower, Henry Kauz, Lin Liao, Don Patterson - 2003
Robust Localization of Persons Based on Learned Motion Patterns – Grzegorz Cielniak Maren, Maren Bennewitz, Wolfram Burgard
Learning Hierarchical Models of Activity – Sarah Osentoski Victoria - 2004
Predicting Driving Speed using Neural Networks – Stefan Schroedl And
A Formal Mathematical Framework for – Modeling Probabilistic Hybrid