Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Features and classification methods to locate deciduous trees in images
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A study of cloud classification with neural networks using spectral and textural features
IEEE Transactions on Neural Networks
Classification of heart sounds using an artificial neural network
Pattern Recognition Letters
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A novel hybrid neural network trained by the genetic algorithms is presented. Genetic algorithms are used to improve the neural net's classification performance while minimizing the number of nodes. Each node of the network forms a closed region in the input space. The closed regions, which are formed by the nodes, intersect each other. The performance of the proposed hybrid neural network is compared with the multilayer perceptron, and the restricted Coulomb energy network for the segmentation of MR and CT head images. Experimental results show that the proposed neural network gives the best classification performance with a small number of nodes in short training times.