Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9931
Title: Handwritten Character Recognition and Digit Character Recognition using Deep Learning
Authors: Gupta, Manish
Abhishek
Modi, Praveen [Guided by]
Keywords: Digita character recognition
Deep learning
Neural network
Artificial intelligence
Issue Date: 2023
Publisher: Jaypee University of Information Technology, Solan, H.P.
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.
Description: Enrolment No. 191553, 191553
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9931
Appears in Collections:B.Tech. Project Reports

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