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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM18302

REAL TIME OBJECT DETECTION FOR VISUALLY CHALLENGED PEOPLE USING MACHINE LEARNING

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM18302

Volume:

7 |

3 |

Mar 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PSAK

Prof. Sneha A. Khaire

DN

Dhanraj Nikam

AP

Ajinkya Pawar

CD

Chaitanya Devkar

SP

Shubham Pagar

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Abstract

The latest generation of mobile phones have excellent hardware capabilities and quicker processing, which are strong enough to enable the creation of applications that enable users to connect and engage with the outside world at their own pace. This system reads OCR and utilizes the camera app on your smartphone in addition to the camera. Optical Character Recognition (OCR) is a tool that converts printed, handwritten, or typed text into machine-readable text from a picture. This system will assist you in taking a photo of or scanning a document that is currently in your possession using the camera on your phone. After the image has been scanned, an application will read any English-language text and turn the results into speech. The speech communication channel is regarded by the authors as one of the most crucial modalities to help the blind and low vision people in the state-of-the-art accessibility area.

KEYWORDS

OCR camera app speech blind vision

Cite This Article

Prof. Sneha A. Khaire, Dhanraj Nikam, Ajinkya Pawar, Chaitanya Devkar, Shubham Pagar, "REAL TIME OBJECT DETECTION FOR VISUALLY CHALLENGED PEOPLE USING MACHINE LEARNING," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 3, Mar 2023. https://doi.org/10.55041/IJSREM18302

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Publication Date

3/24/2023

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Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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