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Image classification, support vector machine, artificial neural network
Image classification is one of classical problems of concern in image processing. There are various approaches for solving this problem. The aim of this paper is bring together two areas in which are Artificial Neural Network (ANN) and Support Vector Machine (SVM) applying for image classification. Firstly, we separate the image into many sub-images based on the features of images. Each sub-image is classified into the responsive class by an ANN. Finally, SVM has been compiled all the classify result of ANN. Our proposal classification model has brought together many ANN and one SVM. Let it denote ANN_SVM. ANN_SVM has been applied for Roman numerals recognition application and the precision rate is 86%. The experimental results show the feasibility of our proposal model.
Le Hoang Thai, Tran Son Hai, Nguyen Thanh Thuy, "Image Classification using Support Vector Machine and Artificial Neural Network", International Journal of Information Technology and Computer Science(IJITCS), vol.4, no.5, pp.32-38, 2012. DOI:10.5815/ijitcs.2012.05.05
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