INTERPRETING DOCTORS NOTES USING HANDWRITING RECOGNITION AND DEEP LEARNING TECHNIQUES

Computer Engineering

Handwritten recognition is becoming one of the most researched areas in the field of computer science. As the technologies are growing, everyone wants advanced life, which makes life easier. Even in the recognition of handwriting, mainly doctors notes, they are very difficult for everyone to understand and it takes time for a person to analyse it. So, this paper mainly focused on interpreting doctor’s notes using handwritten recognition and deep learning techniques. The handwritten or printed document pictures are transformed into their electronic counterparts using an optical character recognition (OCR) system. Due to individuals' inconsistent writing styles, dealing with handwritten texts is significantly more difficult than dealing with printed ones. Handwritten text recognition could be done by Image processing, Machine Learning or Deep Learning Techniques. Out of these Deep Learning remains to be the most popular and prominent. Some of the Deep Learning techniques includes Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs). This paper gives a review of the various recognition methodologies used for interpreting handwritten texts. This paper includes the most important algorithms that could be used for detecting the handwritten word/text/character by using various approaches for the recognition process. In the end we are thus comparing the accuracies provided by these systems.

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