Abstract. Learning-based approaches have become increasingly practical in medical imaging. For a supervised learning strategy, the quality of the trained algorithm (usually a class...
Juan Eugenio Iglesias, Cheng-Yi Liu, Paul M. Thomp...
—The online detection of anomalies is a vital element of operations in data centers and in utility clouds like Amazon EC2. Given ever-increasing data center sizes coupled with th...
Fixing concurrency bugs (or crugs) is critical in modern software systems. Static analyses to find crugs such as data races and atomicity violations scale poorly, while dynamic a...
Guoliang Jin, Aditya V. Thakur, Ben Liblit, Shan L...
—This paper addresses pattern classification in the framework of domain adaptation by considering methods that solve problems in which training data are assumed to be available o...
—A spatiotemporal saliency algorithm based on a center-surround framework is proposed. The algorithm is inspired by biological mechanisms of motion-based perceptual grouping and ...