FruitVision: A deep learning based automatic fruit grading system

被引：2

作者：

Hayat, Ahatsham ^{[1
,2
,3
,4
]}

Morgado-Dias, Fernando ^{[2
,3
,4
]}

Choudhury, Tanupriya ^{[5
,6
]}

Singh, Thipendra P. ^{[7
]}

Kotecha, Ketan ^{[8
]}

机构：

[1] Univ Nebraska Lincoln, Dept Elect & Comp Engn, Lincoln, NE 68588 USA

[2] Univ Madeira, P-9000082 Funchal, Portugal

[3] Interact Technol Inst ITI LARSyS, P-9020105 Funchal, Portugal

[4] ARDITI, P-9020105 Funchal, Portugal

[5] Era Graph Era Univ Dehradun, CSE Dept, Dehra Dun 248002, Uttarakhand, India

[6] Symbiosis Int Deemed Univ SIU, Symbiosis Inst Technol, CSE Dept, Lavale Campus, Pune 412115, Maharashtra, India

[7] Bennett Univ, Sch Comp Sci Engn & Technol, Greater Noida, Ncr, India

[8] Symbiosis Int Deemed Univ SIU, Symbiosis Inst Technol, Symbiosis Ctr Appl Artificial Intelligence SCAAI, Pune 412115, Maharashtra, India

来源：

OPEN AGRICULTURE | 2024年 / 9卷 / 01期

关键词：

machine learning; computer vision; deep learning; fruit grading; agriculture; COMPUTER VISION; CLASSIFICATION; COLOR; AGRICULTURE; TEXTURE;

D O I：

10.1515/opag-2022-0276

中图分类号：

S [农业科学];

学科分类号：

09 ;

摘要：

Quality assessment of fruits plays a key part in the global economy's agricultural sector. In recent years, it has been shown that fruits are affected by different diseases, which can lead to widespread economic failure in the agricultural industry. Traditional manual visual grading of fruits could be more accurate, making it difficult for agribusinesses to assess quality efficiently. Automatic grading of fruits using computer vision has become a prominent area of study for many researchers. In this study, a deep learning-based model called FruitVision is proposed for the automatic grading of various fruits. The results showed that FruitVision performed all the existing models and obtained an accuracy of 99.42, 99.50, 99.24, 99.12, 99.38, 99.38, 99.17, 98.86, and 97.96% for the apple, banana, guava, lime, orange, pomegranate, Ajwa date, Mabroom date, and mango, respectively, using 5-fold cross-validation. This is a remarkable achievement in the field of AI-based fruit grading systems.

引用

页数：17

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