As devices are scaled to the nanoscale regime, it is clear that future nanodevices will be plagued by higher soft error rates and reduced noise margins. Traditional implementation...
Kundan Nepal, R. Iris Bahar, Joseph L. Mundy, Will...
The provenance of data has recently been recognized as central to the trust one places in data. It is also important to annotation, to data integration and to probabilistic databa...
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Tracking of multiple objects in biological image data is a challenging problem due largely to poor imaging conditions and complicated motion scenarios. Existing tracking algorithm...
— This paper presents a general framework for multi-sensor object recognition through a discriminative probabilistic approach modelling spatial and temporal correlations. The alg...