REVOLUTIONIZING TEXT RECOGNITION: EXPLORING OPTICAL CHARACTER RECOGNITION WITH CUTTING-EDGE CNN TECHNIQUES

Volume 9, Issue 3, June 2024     |     PP. 60-72      |     PDF (233 K)    |     Pub. Date: August 31, 2024
DOI: 10.54647/computer520419    23 Downloads     2318 Views  

Author(s)

Kodeti Haritha Rani, Kodeti Haritha Rani, Research Scholar, Department of Computer Science and Engineering,Lincoln University college,Malaysia
Midhun Chakkaravarthy, Midhun Chakkravarthy,Associate Professor, Department of Computer Science and Engineering, Lincoln University college,Malaysia

Abstract
In the era of digitization, Optical Character Recognition (OCR) technology plays a pivotal role in transforming printed or handwritten text into machine-readable data. This abstract delves into the realm of text recognition, exploring the revolutionary advancements brought about by Convolutional Neural Networks (CNNs) in the field of OCR. This article illuminates the fundamental principles underlying CNNs and their application in OCR, emphasizing their ability to automatically learn intricate features from input images, enabling unparalleled accuracy in character recognition. The abstract concludes by contemplating the future of OCR, envisaging the integration of CNN techniques with emerging technologies like natural language processing and reinforcement learning. this abstract serves as a gateway to the transformative realm of OCR powered by cutting-edge CNN techniques.

Keywords
Optical Character Recognition, Text Recognition, Convolutional Neural Networks, Deep Learning, Cutting-Edge CNN Techniques.

Cite this paper
Kodeti Haritha Rani, Midhun Chakkaravarthy, REVOLUTIONIZING TEXT RECOGNITION: EXPLORING OPTICAL CHARACTER RECOGNITION WITH CUTTING-EDGE CNN TECHNIQUES , SCIREA Journal of Computer. Volume 9, Issue 3, June 2024 | PP. 60-72. 10.54647/computer520419

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