Computer Intelligence-Based Fruit Grading: A Review

4Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Ratha, A. K., Barpanda, N. K., Sethy, P. K., Sharada, G., & Behera, S. K. (2023, April 1). Computer Intelligence-Based Fruit Grading: A Review. Revue d’Intelligence Artificielle. International Information and Engineering Technology Association. https://doi.org/10.18280/ria.370223

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free