—The feature selection phase is one of the first, and yet very important, tasks to be completed during the development of any Intrusion Detection System. If this phase is neglec...
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, ...
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
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...
We extend the successful 2D robust feature concept into the third dimension in that we produce a descriptor for a reconstructed 3D surface region. The descriptor is perspectively ...