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HYBRID MACHINE LEARNING IN CLASSIFICATION METHODS FOR HCR IN GUJARATI LANGUAGE

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dc.contributor.author PRIYANK D. DOSHI, DR.PRATIK VANJARA
dc.date.accessioned 2024-11-22T05:45:17Z
dc.date.available 2024-11-22T05:45:17Z
dc.date.issued 2022
dc.identifier.uri http://10.9.150.37:8080/dspace//handle/atmiyauni/1902
dc.description.abstract The problem of recognizing Gujarati Handwritten character with vowels opening new future scope where one can use smart phone, website or any handy scanner to convert hand written Gujarati Language into text. It will be very effective to give education in mother language at primary level. Public, Private and Government sectors will be benefited when they get any hand written Guajarati Script and they can directly convert it into softcopy or into text form. There are many methods used to solve this problem.Using CNN we can improve new algorithm depending on training data set, mathematical model and other intricacy. Convolutional Neural Network or machine learning is very useful for this. Still there are more chances for improvement and rising accuracy using Machine learning in combination of Deep Learning as a hybrid model en_US
dc.language.iso en en_US
dc.subject MACHINE LEARNING en_US
dc.subject CONVOLUTIONAL NEURAL NETWORK en_US
dc.subject SUPPORT VECTOR MACHINE en_US
dc.subject HAND WRITTEN CHARACTER RECOGNITION (HCR en_US
dc.subject ARTIFICIAL NEURAL NETWORK (ANN) en_US
dc.title HYBRID MACHINE LEARNING IN CLASSIFICATION METHODS FOR HCR IN GUJARATI LANGUAGE en_US
dc.type Article en_US


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