HANDWRITING RECOGNITION USING CNN

The recognition and discovery of handwriting has become an important subject in modern times. Human handwriting can be easily hidden in a variety of ways including free handwriting, image tracking and transfer, making real manuscript recognition still a challenging task but recognition of English words lacks simplicity and accuracy. Although it's diagnostic method is well reported, good deception can outperform existing tools. Existing recognition systems have led to many research activities in automated detection and recognition tasks using computer techniques, feature extraction, class comparisons, performance testing and pattern recognition. To simplify, simplify English writing, simplicity and efficiency, we are developing a handwriting acquisition and recognition system based on CNN's in-depth learning model.