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» A theoretical framework for multiple neural network systems
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AIIA
2003
Springer
14 years 15 days ago
A Neural Architecture for Segmentation and Modelling of Range Data
A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neu...
Roberto Pirrone, Antonio Chella
CEC
2010
IEEE
13 years 10 months ago
An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
Jean-François Connolly, Eric Granger, Rober...
FPL
2009
Springer
161views Hardware» more  FPL 2009»
14 years 1 months ago
A multi-FPGA architecture for stochastic Restricted Boltzmann Machines
Although there are many neural network FPGA architectures, there is no framework for designing large, high-performance neural networks suitable for the real world. In this paper, ...
Daniel L. Ly, Paul Chow
JMLR
2006
389views more  JMLR 2006»
13 years 8 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
CDC
2008
IEEE
168views Control Systems» more  CDC 2008»
14 years 3 months ago
An information-driven framework for motion planning in robotic sensor networks: Complexity and experiments
Abstract— A geometric optimization based approach to deploy a mobile sensor network for the purpose of detecting and capturing mobile targets in the plane is presented in [1]. Th...
Rafael Fierro, Silvia Ferrari, Chenghui Cai