In medical image analysis, the image content is often represented by computed features that need to be interpreted at a clinical level of understanding to support lopment of clini...
Birgit Lessmann, Tim W. Nattkemper, V. H. Hans, An...
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
Relation extraction is the task of finding semantic relations between entities from text. The state-of-the-art methods for relation extraction are mostly based on statistical lea...
Feature models are widely used to model software product-line (SPL) variability. SPL variants are configured by selecting feature sets that satisfy feature model constraints. Conf...
Jules White, Douglas C. Schmidt, David Benavides, ...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...