AMachine Learning and Deep Learning Approach for Recognizing Handwritten Digits

Optical character recognition (OCR) can be a subcategory of graphic design that involves extracting text from images or scanned documents. We have chosen to make unique handwritten digits available on the Modified National Institute of Standards and Technology website for this project. The Machine Learning and Depp Learning algorithms are used in this project to measure the accuracy of handwritten displays of letters and numbers. Also, we show the classification accuracy comparison between them. The results showed that the CNN classifier achieved the highest classification accuracy of 98.83%.

Automated summary

Optical character recognition (OCR) is utilized in this project to extract text from images or scanned documents. The accuracy of handwritten displays of letters and numbers is measured using Machine Learning and Deep Learning algorithms, with a comparison of classification accuracy shown. The CNN classifier achieved the highest classification accuracy of 98.83%.