Accurate and precise estimation of the noise variance is often of key importance as an input parameter for posterior image processing tasks. In MR images, background data is well s...
Data compression and prediction are closely related. Thus prediction methods based on data compression algorithms have been suggested for the branch prediction problem. In this wo...
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rule-based methods. In this paper, we presen...
Saliency estimation has become a valuable tool in image processing. Yet, existing approaches exhibit considerable variation in methodology, and it is often difficult to attribute...