We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
We present a new adaptive sampling strategy for ray tracing. Our technique is specifically designed to handle multidimensional sample domains, and it is well suited for efficientl...
Toshiya Hachisuka, Wojciech Jarosz, Richard Peter ...
Context-based adaptive entropy coding is an essential feature of modern image compression algorithms; however, the design of these coders is non-trivial due to the balance that mu...
Recent developments in bio-photonics have called for the need of bringing cellular and molecular imaging modalities to an in vivo ? in situ setting to allow for real-time tissue ch...
Selen Atasoy, David P. Noonan, Selim Benhimane, ...
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...