Constraint networks have been shown to be useful in formulating such diverse problems as scene labeling, natural language parsing, and temporal reasoning. Given a constraint netwo...
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
This paper presents TiNA, a scheme for minimizing energy consumption in sensor networks by exploiting end-user tolerance to temporal coherency. TiNA utilizes temporal coherency to...
Mohamed A. Sharaf, Jonathan Beaver, Alexandros Lab...
Given a spatio-temporal network (ST network) whose edge properties vary with time, a time-sub-interval minimum spanning tree (TSMST) is a collection of distinct minimum spanning t...
Wireless sensor networks have created new opportunities for data collection in a variety of scenarios, such as environmental and industrial, where we expect data to be temporally ...