Handwritten Character Recognition using Deep Learning | Zendy

Bhargav Rajyagor | Zendy; Rajnish Rakholia | Zendy

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Handwritten Character Recognition using Deep Learning

Author(s) -

Bhargav Rajyagor,

Rajnish Rakholia

Publication year - 2020

Publication title -

international journal of recent technology and engineering (ijrte)

Language(s) - English

Resource type - Journals

ISSN - 2277-3878

DOI - 10.35940/ijrte.f8608.038620

Subject(s) - computer science , character (mathematics) , intelligent character recognition , character recognition , artificial intelligence , focus (optics) , document processing , optical character recognition , intelligent word recognition , deep learning , speech recognition , feature (linguistics) , field (mathematics) , set (abstract data type) , pattern recognition (psychology) , natural language processing , feature extraction , image (mathematics) , linguistics , philosophy , physics , geometry , mathematics , pure mathematics , optics , programming language

In day to day human life, handwritten documents are a general purpose for communication and restoring their information. In the field of computer science, character recognition using Deep Learning has more attention. DL has a massive set of pattern recognition tools that can apply to speech recognition, image processing, natural language processing and has a remarkable capability to find out a solution for complex machine learning problems. DL can focus on the specific feature of an image to character recognition for enhancing efficiency and accuracy.

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