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» Training Methods for Adaptive Boosting of Neural Networks
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ICIP
2003
IEEE
15 years 11 months ago
Compressed domain human motion recognition using motion history information
In this paper we present a system for classifying various human actions in compressed domain video framework. We introduce the notion of quantifying the motion involved, through w...
R. Venkatesh Babu, K. R. Ramakrishnan
IJCNN
2008
IEEE
15 years 4 months ago
Active Meta-Learning with Uncertainty Sampling and Outlier Detection
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
ICTAI
2006
IEEE
15 years 3 months ago
Modeling and Recognition of Gesture Signals in 2D Space: A Comparison of NN and SVM Approaches
In this paper we introduce a novel technique for modeling and recognizing gesture signals in 2D space. This technique is based on measuring the direction of the gradient of the mo...
Farhad Dadgostar, Abdolhossein Sarrafzadeh, Chao F...
ICRA
2005
IEEE
102views Robotics» more  ICRA 2005»
15 years 3 months ago
Hand Force Estimation using Electromyography Signals
— In many studies and applications that include direct human involvement such as human-robot interaction, control of prosthetic arms, and human factor studies, hand force is need...
Farid Mobasser, Keyvan Hashtrudi-Zaad
ICRA
1998
IEEE
141views Robotics» more  ICRA 1998»
15 years 1 months ago
On Discontinuous Human Control Strategies
Models of human control strategy (HCS), which accurately emulate dynamic human behavior, have far reaching potential in areas ranging from robotics to virtual reality to the intel...
Michael C. Nechyba, Yangsheng Xu