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Handwritten digit recognition using computer vision

Abstract:
Recognition of handwritten digits has a significant influence on deep learning applications. Deep learning is mostly utilised in the field of object identification, and convolutional neural networks have emerged as one of the key techniques and key contributors to several successes in recent years. The speech output capability is merged with the text output in the written work. The categorization of images using a convolutional neural network model. The MNIST dataset was utilised for both training and testing. Real-time handwritten digit recognition has many different uses. It is used in the reading of bank checks, the identification of car numbers, and the organisation of mail at the post office.

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