This paper investigates the decentralized detection of Hidden Markov Processes using the NeymanPearson test. We consider a network formed by a large number of distributed sensors....
Joffrey Villard, Pascal Bianchi, Eric Moulines, Pa...
This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely con...
Abstract This paper focuses on human behavior recognition where the main problem is to bridge the semantic gap between the analogue observations of the real world and the symbolic ...
Abstract This paper presents an approach to designing and implementing extensible computational models for perceiving systems based on a knowledge-driven joint inference approach. ...
Wide-area sensor infrastructures, remote sensors, RFIDs, and wireless sensor networks yield massive volumes of disparate, dynamic, and geographically distributed data. As such sen...
Ranga Raju Vatsavai, Olufemi A. Omitaomu, Joao Gam...