Ever since the first fishermen ventured into the sea, tides have been the subject of intense human observation. As a result computational models and ‘tide predicting machines...
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) is often based on approaches like gradient ascent, attractive because of their ...
This paper presents a novel approach to the multi-vehicle Simultaneous Localisation and Mapping (SLAM) problem that exploits the manner in which observations are fused into the gl...
Stefan B. Williams, Gamini Dissanayake, Hugh F. Du...
In this paper we describe a method to learn parameters
which govern pedestrian motion by observing video
data. Our learning framework is based on variational
mode learning and a...
We propose a canonical model for object classes in aerial images. This model is motivated by the observation that geographic regions of interest are characterized by collections o...