Intelligent fruit quality classification system using transfer learning Article Swipe

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Vikas Khullar , Mohit Angurala , Abhineet Anand , Jagdish Chandra Patni , Harjit Singh ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.32629/jai.v7i4.1424

Amidst the burgeoning demands of fruit agriculturists and grading companies for enhanced fruit quality classification, this research presents a cutting-edge approach to binary fruit quality assessment. We built a portable device for exact fruit quality inspection using transfer learning, a deep learning approach, resulting in a decrease in both human and machine labor. The performance of the system is validated and evaluated under real-time situations, with an emphasis on end-user applicability. This paper rigorously validates and assesses the system’s performance in real-world scenarios, with a strong focus on its practicality for end-users. The model is trained on an online picture dataset that is divided into two categories: ‘good’ and ‘poor’ fruits. On dataset 1, our numerical findings show outstanding classification accuracies of 99.49% and 99.75% for the first and second models, respectively. Meanwhile, on dataset 2, the first and second models attain accuracies of 85.43% and 96.75%, respectively, highlighting the efficacy of our technique.

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Transfer of learning Quality (philosophy) Computer science Artificial intelligence Machine learning Physics Quantum mechanics

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Type: article
Language: en
Landing Page: https://doi.org/10.32629/jai.v7i4.1424
OA Status: diamond
Cited By: 2
Related Works: 10
OpenAlex ID: https://openalex.org/W4392733688

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DOI: https://doi.org/10.32629/jai.v7i4.1424

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Title: Intelligent fruit quality classification system using transfer learning

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Type: article

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Language: en

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Publication year: 2024

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Publication date: 2024-02-07

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Authors: Vikas Khullar, Mohit Angurala, Abhineet Anand, Jagdish Chandra Patni, Harjit Singh

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Landing page: https://doi.org/10.32629/jai.v7i4.1424

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OA status: diamond

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OA URL: https://doi.org/10.32629/jai.v7i4.1424

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Concepts: Transfer of learning, Quality (philosophy), Computer science, Artificial intelligence, Machine learning, Physics, Quantum mechanics

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Cited by: 2

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Citations by year (recent): 2025: 1, 2024: 1

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