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» Robotic Grasping of Novel Objects using Vision
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CVPR
2006
IEEE
14 years 11 months ago
Supervised Learning of Edges and Object Boundaries
Edge detection is one of the most studied problems in computer vision, yet it remains a very challenging task. It is difficult since often the decision for an edge cannot be made ...
Piotr Dollár, Zhuowen Tu, Serge Belongie
CVPR
2007
IEEE
14 years 11 months ago
OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning
A well-built dataset is a necessary starting point for advanced computer vision research. It plays a crucial role in evaluation and provides a continuous challenge to stateof-the-...
Li-Jia Li, Gang Wang, Fei-Fei Li 0002
CRV
2005
IEEE
191views Robotics» more  CRV 2005»
14 years 2 months ago
Automated Behavioral Phenotype Detection and Analysis Using Color-Based Motion Tracking
The problem of elucidating the functional significance of genes is a key challenge of modern science. Solving this problem can lead to fundamental advancements across multiple are...
Alan Shimoide, Ilmi Yoon, Megumi Fuse, Holly C. Be...
ICRA
2009
IEEE
204views Robotics» more  ICRA 2009»
14 years 3 months ago
A high-speed multi-GPU implementation of bottom-up attention using CUDA
— In this paper a novel implementation of the saliency map model on a multi-GPU platform using CUDA technology is presented. The saliency map model is a wellknown computational m...
Tingting Xu, Thomas Pototschnig, Kolja Kühnle...
AAAI
2012
11 years 11 months ago
Model Learning and Real-Time Tracking Using Multi-Resolution Surfel Maps
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
Jörg Stückler, Sven Behnke