— In this paper we create a framework to model and characterize the impact of time-varying fading communication links on the performance of a mobile sensor network. We propose co...
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
Abstract—Traditionally, performance has been the most important metrics when evaluating a system. However, in the last decades industry and academia have been paying increasing a...
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...