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IJCNN
2000
IEEE
14 years 1 months ago
People Recognition and Pose Estimation in Image Sequences
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...
Chikahito Nakajima, Massimiliano Pontil, Tomaso Po...
IJCNN
2000
IEEE
14 years 1 months ago
A Training Method with Small Computation for Classification
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...
Kazuyuki Hara, Kenji Nakayama
IJCNN
2000
IEEE
14 years 1 months ago
Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons
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...
Sander M. Bohte, Johannes A. La Poutré, Joo...
IJCNN
2000
IEEE
14 years 1 months ago
Frequency-Based Error Back-Propagation in a Cortical Network
Rafal Bogacz, Malcolm W. Brown, Christophe G. Gira...
IJCNN
2000
IEEE
14 years 1 months ago
Pose Classification Using Support Vector Machines
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
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
14 years 1 months ago
The baldwin effect in developing neural networks
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Keith L. Downing
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
14 years 1 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
GECCO
2006
Springer
141views Optimization» more  GECCO 2006»
14 years 1 months ago
Coevolution of neural networks using a layered pareto archive
The Layered Pareto Coevolution Archive (LAPCA) was recently proposed as an effective Coevolutionary Memory (CM) which, under certain assumptions, approximates monotonic progress i...
German A. Monroy, Kenneth O. Stanley, Risto Miikku...
GECCO
2006
Springer
132views Optimization» more  GECCO 2006»
14 years 1 months ago
A neural evolutionary approach to financial modeling
This paper presents an approach to the joint optimization of neural network structure and weights which can take advantage of backpropagation as a specialized decoder. The approac...
Antonia Azzini, Andrea Tettamanzi