Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9930
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dc.contributor.authorGupta, Manish-
dc.contributor.authorAbhishek-
dc.contributor.authorModi, Praveen [Guided by]-
dc.date.accessioned2023-09-11T05:54:46Z-
dc.date.available2023-09-11T05:54:46Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9930-
dc.descriptionEnrolment No. 191553, 191441en_US
dc.description.abstractHandwritten character recognition and digit character recognition are important tasks in image processing and machine learning. Deep learning techniques have shown great success in achieving high accuracy in these tasks, especially with the use of Convolutional Neural Networks (CNNs). CNNs are a type of deep neural network that can effectively learn and extract features from images. They are well suited for image classification tasks, as they can detect patterns and features at different levels of abstraction. In handwritten character recognition and digit character recognition, CNNs can be used to learn and recognize the unique features of each character or digit.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectNeural networksen_US
dc.subjectArtificial intelligenceen_US
dc.subjectOptical character recognitionen_US
dc.titleHandwritten Character Recognition and Digit Character Recognition using Deep Learningen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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