Bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with ef?cient algorithms for inference and learning. Ear...
Tanzeem Choudhury, James M. Rehg, Vladimir Pavlovi...
Randomly connecting networks have proven to be universal computing machines. By interconnecting a set of nodes in a random way one can model very complicated non-linear dynamic sy...
The RF-SLISSOM model integrates two separate lines of research on computational modeling of the visual cortex. Laterally connected self-organizing maps have been used to model how...
This paper presents a Connectivity based Partition Approach (CPA) to reduce the energy consumption of a sensor network by sleep scheduling among sensor nodes. CPA partitions sensor...
In this paper, we propose a multimodal system for detecting human activity and interaction patterns in a nursing home. Activities of groups of people are firstly treated as intera...