An system-level power management technique for massively distributed wireless microsensor networks is proposed. A power aware sensor node model is introduced which enables the embe...
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
As distributed surveillance networks are deployed over larger areas and in increasingly busy environments, limiting the computation, bandwidth, and human attention burdens imposed...
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...