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» A Neural Model of Human Object Recognition Development
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NECO
2007
127views more  NECO 2007»
13 years 7 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado
ECCV
2008
Springer
14 years 9 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
ICASSP
2008
IEEE
14 years 2 months ago
Recognition for synthesis: Automatic parameter selection for resynthesis of emotional speech from neutral speech
One of the biggest challenges in emotional speech resynthesis is the selection of modification parameters that will make humans perceive a targeted emotion. The best selection me...
Murtaza Bulut, Sungbok Lee, Shrikanth Narayanan
ICRA
2005
IEEE
144views Robotics» more  ICRA 2005»
14 years 1 months ago
Hill-Based Model as a Myoprocessor for a Neural Controlled Powered Exoskeleton Arm - Parameters Optimization
— The exoskeleton robot, serving as an assistive device worn by the human (orthotic), functions as a humanamplifier. Setting the human machine interface (HMI) at the neuro-muscu...
Ettore Cavallaro, Jacob Rosen, Joel C. Perry, Step...
FGR
2006
IEEE
144views Biometrics» more  FGR 2006»
14 years 1 months ago
A Layered Deformable Model for Gait Analysis
In this paper, a layered deformable model (LDM) is proposed for human body pose recovery in gait analysis. This model is inspired by the manually labeled silhouettes in [6] and it...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...