DC Field | Value | Language |
---|---|---|
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 |
Appears in Collections: | 01. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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307) 22079_Pratik Anilkumar Vanjara.pdf | 1.09 MB | Adobe PDF | View/Open |
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