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this paper presents a face recognition method based on correspondence analysis (CA) and trained artificial neural network. In this algorithm, features are extracted using CA, then these features are fed to Multi layer Perceptron (MLP)network for classification and finally, after training the network, effective features are selected with UTA algorithm. The(More)
The ability of Multi-Layer Perceptron (MLP) and Neuro-Fuzzy neural networks to classify corn seed varieties based on mixed morphological and color Features has been evaluated that would be helpful for automation of corn handling. corn varieties were grown in different environments of Iran. A total of 12 color features, 11 morphological features and 4 shape(More)
Artificial neural networks (ANNs) have many applications in various scientific areas such as identification, prediction and image processing. classification of 5 main rice grain varieties grown in different environments in Iran. Classification was made in terms of 24 color features, 11 morphological features and 4 shape factors that were extracted from(More)
Artificial neural network (ANN) models have found wide applications, including prediction, classification, system modeling and image processing. In order to identify of rain fed barely seed cultivars using artificial neural network with different neuron numbers of hidden layers, this research done in Islamic Azad University, Shahr-e-Ray Branch, during 2010(More)
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