U L F G R E N A N D E R
R E S E A R C H I N T E R E S T S
Brain anatomy, a subset of digital anatomy,
at the moment plays a major role in my research.
Digital anatomy in general, and brain anatomy in particular,
is intended to represent and process anatomical patterns in
3D observed with CT, MR, and PET, as well as to facilitate
automatic recognition and component measurement of
Automatic target detection/recognition (ATR) is another topic of interest.
The research primarily involves developing
jump-diffusion algorithms for pattern inference
based on knowledge about the vehicle dynamics and the physics of the sensors.
Computer vision can be studied from the pattern theory
perspective, shape modeling in particular.
In this approach templates are deformed by
Lie groups of transformations.
Natural language lends itself nicely for representation by
stochastic models. Our focus is on mathematical representations
of colloquial language. Of special interest to us are connector
graphs with cycles.
Non-numeric pattern theory for representing knowledge about history,
literature, social systems.
A selection of Matlab files related to computer vision are included in the
gzipped tar file seeing.tar.gz or
you can browse the files individually.
Division of Applied Mathematics
182 George Street
Providence, RI 02912