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Recognizing images of handwritten digits using learning vector quantization artificial neural network

Recognizing the digits has become an integral part in terms of real world applications. Since, digits are written in different styles therefore to identify the digit it is necessary to recognize and classify it with the help of machine learning techniques. This research is based on supervised learning vector quantization neural network categorized under artificial neural network. The images of digits are recognized, trained and tested. After the network is created digits are trained using training dataset vectors and testing is applied to the images of digits which are isolated to each other by segmenting the image and resizing the digit image accordingly for better accuracy.