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DC Field | Value | Language |
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dc.contributor.author | Gupta, Manish | - |
dc.contributor.author | Abhishek | - |
dc.contributor.author | Modi, Praveen [Guided by] | - |
dc.date.accessioned | 2023-09-11T05:54:46Z | - |
dc.date.available | 2023-09-11T05:54:46Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9930 | - |
dc.description | Enrolment No. 191553, 191441 | en_US |
dc.description.abstract | Handwritten 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.iso | en_US | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Artificial intelligence | en_US |
dc.subject | Optical character recognition | en_US |
dc.title | Handwritten Character Recognition and Digit Character Recognition using Deep Learning | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Handwritten Character Recognition and Digit Character Recognition using Deep Learning.pdf | 873.62 kB | Adobe PDF | View/Open |
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