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This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
This paper presents a system which learns from examples to automatically recognize people and estimate their poses in image sequences with the potential application to daily surve...
A training data selection method for multi-class data is proposed. This method can be used for multilayer neural networks (MLNN). The MLNN can be applied to pattern classification...
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
The field of human-computer interaction has been widely investigated in the last years, resulting in a variety of systems used in different application fields like virtual reality...
Edoardo Ardizzone, Antonio Chella, Roberto Pirrone
This w orkshows how to train the activation function in neuro-wavelet parametric modeling and how this improves performance in a number of modeling, classi cation and forecasting.
Valentina Colla, Mirko Sgarbi, Leonardo Maria Reyn...
In this paper, we propose a neural-network approach for visual authorization. It is an application on visual cryptography. The scheme contains a key-share and a set of user-shares....
In this paper the popular PD controller of robot manipulator is modified. RBF neural networks are used to compensate the gravity and fi-iction. No exact knowledge of the robot dyn...