This paper provides a mathematical analysis of transform compression in its relationship to linear and nonlinear approximation theory. Contrasting linear and nonlinear approximatio...
Albert Cohen, Ingrid Daubechies, Onur G. Guleryuz,...
The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
We examine frequency-domain issues in the design and selection of on-chip test generators for built-in self-test (BIST) of highperformance digital filters. Test-generator/circuit...
We introduce an exemplar model that can learn and generate a region of interest around class instances in a training set, given only a set of images containing the visual class. T...
Summarizing the contents of a video containing human activities is an important problem in computer vision and has important applications in automated surveillance systems. Summar...