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» Scalable learning for object detection with GPU hardware
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IROS
2009
IEEE
198views Robotics» more  IROS 2009»
13 years 11 months ago
Scalable learning for object detection with GPU hardware
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...
ACCV
2006
Springer
13 years 10 months ago
Boosted Algorithms for Visual Object Detection on Graphics Processing Units
Nowadays, the use of machine learning methods for visual object detection has become widespread. Those methods are robust. They require an important processing power and a high mem...
Hicham Ghorayeb, Bruno Steux, Claude Laurgeau
SIBGRAPI
2006
IEEE
13 years 10 months ago
Hardware-assisted Rendering of CSG Models
Current methods that interactively render reasonably complex CSG objects are image based and are severely bandwidth limited. This paper presents a new approach to raytracing CSG o...
Fabiano Romeiro, Luiz Velho, Luiz Henrique de Figu...
CGF
2010
210views more  CGF 2010»
13 years 4 months ago
Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces
We present a new hybrid CPU/GPU collision detection technique for rigid and deformable objects based on spatial subdivision. Our approach efficiently exploits the massive computat...
Simon Pabst, Artur Koch, Wolfgang Straßer
ASPLOS
2010
ACM
13 years 11 months ago
Accelerating the local outlier factor algorithm on a GPU for intrusion detection systems
The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in...
Malak Alshawabkeh, Byunghyun Jang, David R. Kaeli