Automatic Marks Identification from Test Notes using Deep Learning Algorithm

The process of detecting and categorising handwritten digits into the relevant numerical values is known as handwritten digit recognition. It has numerous practical applications, including optical character recognition (OCR) for digitizing handwritten documents, check processing, and automated mail sorting. The Convolutional Neural Networks (CNNs) is one of the deep learning algorithm that have given impressive results in handwritten digit recognition tasks, achieving accuracy levels close to human performance. These algorithms learn to recognize the patterns and shapes of digits by analyzing large amounts of labeled data and adjusting their weights and biases accordingly. So, to reduce the time-consuming work of entering marks individually, we proposed a system that recognizes the digit in the answer sheet and retrieves it in excel format