Abstract— We consider the problem of robotic object detection of such objects as mugs, cups, and staplers in indoor environments. While object detection has made significant pro...
Adam Coates, Paul Baumstarck, Quoc V. Le, Andrew Y...
Abstract—Detecting and localizing performance faults is crucial for operating large enterprise data centers. This problem is relatively straightforward to solve if each entity (a...
Vaishali P. Sadaphal, Maitreya Natu, Harrick M. Vi...
We propose a new approach to collision and self– collision detection of dynamically deforming objects that consist of tetrahedrons. Tetrahedral meshes are commonly used to repre...
Matthias Teschner, Bruno Heidelberger, Matthias M&...
This paper presents a novel approach for detecting network intrusions based on a competitive learning neural network. In the paper, the performance of this approach is compared to...
—We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-...
Pedro F. Felzenszwalb, Ross B. Girshick, David A. ...