Machine learning algorithms have recently attracted much interest for effective link adaptation due to their flexibility and ability to capture more environmental effects implicitl...
We propose XSEED, a synopsis of path queries for cardinality estimation that is accurate, robust, efficient, and adaptive to memory budgets. XSEED starts from a very small kernel,...
We describe a real-time, low-cost system to localize a mobile robot in outdoor environments. Our system relies on stereo vision to robustly estimate frame-to-frame motion in real ...
In this paper, we explore the concept of using analytical models to efficiently generate delay change curves (DCCs) that can then be used to characterize the impact of noise on an...
Kanak Agarwal, Yu Cao, Takashi Sato, Dennis Sylves...
In this paper we propose a framework of factorization-based non-rigid shape modeling and tracking in stereo-motion. We construct a measurement matrix with the stereo-motion data c...