We investigate the use of an unsupervised artificial neural network to form a sparse representation of the underlying causes in a data set. By using fixed lateral connections that...
We develop, analyze, and evaluate a novel, supervised, specific-to-general learner for a simple temporal logic and use the resulting algorithm to learn visual event definitions fr...
To reduce the semantic gap between low-level visual features and the richness of human semantics, this paper proposes new algorithms, by virtue of the combined camera motion descri...
Today many kinds of postprocessing are used in digital TV receivers or multimedia terminals for video signals to enhance the picture quality. To achieve this the properties of hum...
This paper proposes a method for analyzing and synthesizing video sequences, specifically suited for image sequences of natural phenomena. We combine a low-dimensional representat...