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- W4360909541 abstract "Today, we are living in a world where we are totally surrounded by numbers, the digits, directly or indirectly. The digits are everywhere whether it be your smart phones, latest gadgets, vehicles, technology-oriented infrastructures, etc. Today, we are focusing more and more on the digitalization and automation of almost everything. So now, it becomes very much important to get into the technologies like machine learning, artificial intelligence, deep learning, etc. to classify and recognize those digits. So, in this project, we tried to execute a model which recognizes the digits and makes our tasks and our difficulties very easier. Our model identifies the given digits with an accuracy of 98.40% which is actually great. We are using the convolutional neural network (CNN) to train our model." @default.
- W4360909541 created "2023-03-26" @default.
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- W4360909541 date "2023-01-01" @default.
- W4360909541 modified "2023-09-23" @default.
- W4360909541 title "Handwritten Digit Recognition Using Machine Learning" @default.
- W4360909541 cites W2119448067 @default.
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- W4360909541 doi "https://doi.org/10.1007/978-981-19-7615-5_3" @default.
- W4360909541 hasPublicationYear "2023" @default.
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