Many real life optimization problems are defined in terms of both hard and soft constraints, and qualitative conditional preferences. However, there is as yet no single framework f...
Carmel Domshlak, Steven David Prestwich, Francesca...
In this paper we present a simple framework for activity recognition based on a model of multi-layered finite state machines, built on top of a low level image processing module f...
In low-light conditions, it is known that Poisson noise and quantization noise become dominant sources of noise. While intensity difference is usually measured by Euclidean distanc...
Most tandem mass spectrum identification algorithms use information only from the final spectrum, ignoring precursor information such as peptide retention time (RT). Efforts to exp...
Aaron A. Klammer, Xianhua Yi, Michael J. MacCoss, ...
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...