Handwritten-Digit-Recognition-System-using-a-Convolutional-Neural-Network-in-Python-and-Java

This project addresses the challenge of automated recognition of handwritten digit sequences through a comprehensive two-step approach involving initial digit segmentation and subsequent digit classification using a recognition module. The practical implications span various domains such as mail sorting, bank check processing, and form data entry. The central focus is on developing a robust algorithm capable of efficiently identifying handwritten digits from diverse sources like scanners and digital devices. Handwritten character recognition is one of the practically important issues in pattern recognition applications. The main purpose of this project is to build an automatic handwritten digit recognition method for the recognition of handwritten digit strings. The applications of digit recognition include postal mail sorting, bank check processing, form data entry, etc. The heart of the problem lies within the ability to develop an efficient algorithm that can recognize handwritten digits and which is submitted by users by way of a scanner, tablet, and other digital devices.