Optical Character Recognition is an upcoming field and is much fascination among deep learning researchers.OCR is the conversion of typed or handwritten text into machine-encoded text. It is one of the hardest problems to solve in computer vision and is still an active area of research with no one standard model. OCR is used for recognizing printed text conversion in many areas and was even one of showcased talks in Tensorflow Dev Summit( ) by Coco-Cola.
But what happens when your text consists of a Handwritten description? Handwriting is the most humane form of data available in the world of natural language processing. There are several styles and manner that defines a person's writing.
CNN-RNN architectures in Deep Learning provide a far lower accuracy for predicting such text. I propose a method by combining CNN-NGram and Image Augmentation for recognizing handwritten text. Furthermore, there would be an explanation of how to approach such machine learning problems, i.e from the data collection to pre-processing to the model training and results.
Intel is back in UPES with yet another amazing talk on "Computer Vision Application in Handwriting Detection".
Hurry up! Get your seats booked before it's house full.