Various techniques of system identification exist that provide a nominal model and an uncertainty bound. An important question is what the implications are for the particular choi...
This paper considers the problem of monocular human body tracking using learned models. We propose to learn the joint probability distribution of appearance and body pose using a m...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...
This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifie...
Over the last few years, Real-Time Calculus has been used extensively to model and analyze embedded systems processing continuous data/event streams. Towards this, bounds on the a...
Anne Bouillard, Linh T. X. Phan, Samarjit Chakrabo...
Abstract— Standard embeded sensor nework models emphasize energy efficiency and distributed decision-making by considering untethered and unattended sensors. To this we add two ...
Rajgopal Kannan, Sudipta Sarangi, S. Sitharama Iye...