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» Training Methods for Adaptive Boosting of Neural Networks
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CVPR
2012
IEEE
13 years 23 hour ago
Image denoising: Can plain neural networks compete with BM3D?
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...
AVSS
2007
IEEE
15 years 4 months ago
Face localization by neural networks trained with Zernike moments and Eigenfaces feature vectors. A comparison
Face localization using neural network is presented in this communication. Neural network was trained with two different kinds of feature parameters vectors; Zernike moments and E...
Mohammed Saaidia, Anis Chaari, Sylvie Lelandais, V...
CIMCA
2005
IEEE
15 years 3 months ago
Hybrid Neural Networks for Immunoinformatics
Hybrid set of optimally trained feed-forward, Hopfield and Elman neural networks were used as computational tools and were applied to immunoinformatics. These neural networks ena...
Khrizel B. Solano, Tolja Djekovic, Mohamed Zohdy
NPL
1998
87views more  NPL 1998»
14 years 9 months ago
Constrained Learning in Neural Networks: Application to Stable Factorization of 2-D Polynomials
Adaptive artificial neural network techniques are introduced and applied to the factorization of 2-D second order polynomials. The proposed neural network is trained using a const...
Stavros J. Perantonis, Nikolaos Ampazis, Stavros V...
ACL
2004
14 years 11 months ago
Discriminative Training of a Neural Network Statistical Parser
Discriminative methods have shown significant improvements over traditional generative methods in many machine learning applications, but there has been difficulty in extending th...
James Henderson