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@article{151893,
        author = {Deeksha M Gautam and Pooja Khulbe  and Abhay Srivastava and Vikas Yadav and Virat Raj},
        title = {Handwritten Text Recognition App using Python},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {1161-1166},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151893},
        abstract = {The aim of this research is to offer a new solution or to improvise with the various traditional handwriting recognition techniques. Text recognition is the one in all the emerging fields within the Computer Vision and Deep learning. 
Handwritten text Detection is a technique or ability of a Computer to receive and interpret the handwritten input from a variety of sources such as paper documents, touch screen, photos, etc. The goal of handwriting recognition is to identify input characters or image correctly then analyze to many automated process systems. This will be applied to detect the writings of different format.This automatic recognition of handwritten text can be extremely useful in many applications which currently exists for reading postal addresses, bank check amounts, and forms, etc. where it is necessary to process large volumes of handwritten data and majorly its applications can be far more. 
The aim of the project is to improve existing handwritten character recognition problem and making it more precise.
},
        keywords = {CNN, Handwritten Text Recognition,  MNIST, Keras, Normalization},
        month = {},
        }