When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
The accurate estimation of motion in image sequences is
of central importance to numerous computer vision applications.
Most competitive algorithms compute flow fields
by minimi...
Andreas Wedel, Daniel Cremers, Thomas Pock, Horst ...
We propose a rate-distortion optimized framework to stream scalable bitstreams of 3-D wavelet video stored at the sender to a remote receiver. Based on the source rate-distortion ...
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...
Abstract. Image segmentation in microscopy, especially in interferencebased optical microscopy modalities, is notoriously challenging due to inherent optical artifacts. We propose ...