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» Image classification using hybrid neural networks
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TNN
1998
92views more  TNN 1998»
14 years 9 months ago
Inductive inference from noisy examples using the hybrid finite state filter
—Recurrent neural networks processing symbolic strings can be regarded as adaptive neural parsers. Given a set of positive and negative examples, picked up from a given language,...
Marco Gori, Marco Maggini, Enrico Martinelli, Giov...
104
Voted
BMCBI
2010
149views more  BMCBI 2010»
14 years 9 months ago
A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context
Background: Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex eti...
Ioannis K. Valavanis, Stavroula G. Mougiakakou, Ke...
CAIP
2001
Springer
120views Image Analysis» more  CAIP 2001»
15 years 2 months ago
Texture Feature Extraction and Classification
Texture analysis plays an increasingly important role in computer vision. Since the textural properties of images appear to carry useful information for discrimination purposes, i...
Brijesh Verma, Siddhivinayak Kulkarni
IJCNN
2007
IEEE
15 years 4 months ago
Using Artificial Neural Networks and Feature Saliency Techniques for Improved Iris Segmentation
—One of the basic challenges to robust iris recognition is iris segmentation. This paper proposes the use of a feature saliency algorithm and an artificial neural network to perf...
Randy P. Broussard, Lauren R. Kennell, David L. So...
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