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» Terrain mapping and classification using neural networks
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ICANN
2001
Springer
15 years 2 months ago
Clustering of EEG-Segments Using Hierarchical Agglomerative Methods and Self-Organizing Maps
EEG segments recorded during microsleep events were transformed to the frequency domain and were subsequently clustered without the common summation of power densities in spectral ...
David Sommer, Martin Golz
ICDAR
2003
IEEE
15 years 3 months ago
Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis
Neural networks are a powerful technology for classification of visual inputs arising from documents. However, there is a confusing plethora of different neural network methods th...
Patrice Simard, David Steinkraus, John C. Platt
VLSISP
2002
114views more  VLSISP 2002»
14 years 9 months ago
Image processing using cellular neural networks based on multi-valued and universal binary neurons
Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an a...
Igor N. Aizenberg, Constantine Butakoff
CNSR
2004
IEEE
174views Communications» more  CNSR 2004»
15 years 1 months ago
Network Intrusion Detection Using an Improved Competitive Learning Neural Network
This paper presents a novel approach for detecting network intrusions based on a competitive learning neural network. In the paper, the performance of this approach is compared to...
John Zhong Lei, Ali A. Ghorbani
AI
2002
Springer
14 years 9 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang