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» Learning Object Shape: From Drawings to Images
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TSMC
2008
162views more  TSMC 2008»
15 years 6 months ago
Codevelopmental Learning Between Human and Humanoid Robot Using a Dynamic Neural-Network Model
The paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural network model which is inspired by human parietal cortex functio...
Jun Tani, Ryunosuke Nishimoto, Jun Namikawa, Masat...
ICRA
2008
IEEE
204views Robotics» more  ICRA 2008»
16 years 1 months ago
Active exploration and keypoint clustering for object recognition
— Object recognition is a challenging problem for artificial systems. This is especially true for objects that are placed in cluttered and uncontrolled environments. To challenge...
Gert Kootstra, Jelmer Ypma, Bart de Boer
ICPR
2008
IEEE
16 years 1 months ago
Dyslexia diagnostics by 3D texture analysis of cerebral white matter gyrifications
The importance of accurate early diagnostics of dyslexia that severely affects the learning abilities of children cannot be overstated. Neuropathological studies have revealed an ...
Ayman El-Baz, Manuel Casanova, Georgy L. Gimel'far...
ICCV
2009
IEEE
16 years 11 months ago
Active Skeleton for Non-rigid Object Detection
We present a shape-based algorithm for detecting and recognizing non-rigid objects from natural images. The existing literature in this domain often cannot model the objects ver...
Xiang Bai, Xinggang Wang, Longin Jan Latecki, Weny...
CVPR
2010
IEEE
1135views Computer Vision» more  CVPR 2010»
16 years 2 months ago
Towards Weakly Supervised Semantic Segmentation by Means of Multiple Instance and Multitask Learning.
We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of on...
Alexander Vezhnevets, Joachim Buhmann