We derive a new class of photometric invariants that can be used for a variety of vision tasks including lighting invariant material segmentation, change detection and tracking, a...
Srinivasa G. Narasimhan, Visvanathan Ramesh, Shree...
Despite the flurry of anomaly-detection papers in recent years, effective ways to validate and compare proposed solutions have remained elusive. We argue that evaluating anomaly d...
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
Worst-casebounds on delay and backlog are derived for leaky bucket constrained sessions in arbitrary topology networks of Generalized Processor Sharing (GPS) 10] servers. The inhe...
Abstract-- In this paper, we address the issue of forecasting for periodically measured nonstationary traffic based on statistical time series modeling. Often with time series base...