| Autor: |
Ratha, Ashoka Kumar, Barpanda, Nalini Kanta, Sethy, Prabira Kumar, Sharada, Gowni, Behera, Santi Kumari |
| Předmět: |
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| Zdroj: |
Revue d'Intelligence Artificielle; Apr2023, Vol. 37 Issue 2, p465-474, 10p |
| Abstrakt: |
India is the second-largest fruit producer in the world. But, fruit identification, classification, and grading are carried out manually. Hence, most of the harvested fruit was wasted due to human perception subjectivity because there needed to be more qualified workers. Therefore, the fruit sector must impose an automated fruit detection system to distinguish among different types of fruits based on their variety, class, maturity, and quality. An automated system may be created with the use of appropriate image processing ideas and machine learning strategies for grading and quality inspection of fruits. With an emphasis on the advancement of state-of-the-art, this study provides a quick examination of the methodologies put out in the research publications from the last couple of years. Various methods are used to compare the relevant studies. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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