contact@ijirct.org      

 

Publication Number

2402012

 

Page Numbers

1-4

Paper Details

Real-time Visual Inspection System for Grading Fruits using Computer Vision and Deep Learning Techniques

Authors

R. Sowmiya, K. Praveena Kamal

Abstract

Traditional manual visual grading of fruits has been one of the important challenges faced by the agricultural industry due to its laborious nature as well as inconsistency in inspection and classification process. Automated defects detection using computer vision and machine learning has become a promising area of research with a high and direct impact on the domain of visual inspection. In this study, we propose an efficient and effective machine vision system based on the state-of-the-art deep learning techniques and stacking ensemble methods to offer a non-destructive and cost-effective solution for automating the visual inspection of fruits’ freshness and appearance. We trained, tested and compared the performance of various deep learning models to find the best model for the grading of fruits.

Keywords

 

. . .

Citation

Real-time Visual Inspection System for Grading Fruits using Computer Vision and Deep Learning Techniques. R. Sowmiya, K. Praveena Kamal. 2024. IJIRCT, Volume 10, Issue 6. Pages 1-4. https://www.ijirct.org/viewPaper.php?paperId=2402012

Download/View Paper

 

Download/View Count

23

 

Share This Article