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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
AI Based System For Rotten Fruit Classification And Segregation
Authors
Chitapu Bhavitha Reddy, Marru Hamsika, Konakanchi Sri Radha Madhavi, Gummalla Sindhuja, B. Tulasi Sowjanya
Keywords
AI, CNN, Image Acquisition, Deep learning, Arduino.
Abstract
This paper aims to develop a system for automated classification of rotten fruits using artificial intelligence (AI) and
integrate it with a mechanical arm to segregate. The system will use Deep Learning techniques to analyze the images of fruits and identify the ones that are rotten based on their color, texture, and other visual cues. The data set of images of fruits, both fresh and rotten will be used for training. Once the system is trained, tested and validated it can be used in identifying the freshness of any new fruit given as input to the system. The fruits will be placed before the camera one after the other. The Trained AI Model will classify the images captured by the camera and identify the ones that are rotten. Once the rotten fruit is identified the robotic arm will be activated to separate the rotten fruit from the others.
IJCRT's Publication Details
Unique Identification Number - IJCRT2311021
Paper ID - 245869
Page Number(s) - a153-a159
Pubished in - Volume 11 | Issue 11 | November 2023
DOI (Digital Object Identifier) - http://doi.one/10.1729/Journal.36864
Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Chitapu Bhavitha Reddy, Marru Hamsika, Konakanchi Sri Radha Madhavi, Gummalla Sindhuja, B. Tulasi Sowjanya, "AI Based System For Rotten Fruit Classification And Segregation", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 11, pp.a153-a159, November 2023, Available at :http://www.ijcrt.org/papers/IJCRT2311021.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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