Research Article
Lemon Quality Detection Using CNN
@INPROCEEDINGS{10.4108/eai.23-11-2023.2343188, author={Lekha J and Suryaprabha D and Saraswathi S and Noel Mathew Thomas}, title={Lemon Quality Detection Using CNN}, proceedings={Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India}, publisher={EAI}, proceedings_a={IACIDS}, year={2024}, month={3}, keywords={lemon cnn svm randomforest}, doi={10.4108/eai.23-11-2023.2343188} }- Lekha J
Suryaprabha D
Saraswathi S
Noel Mathew Thomas
Year: 2024
Lemon Quality Detection Using CNN
IACIDS
EAI
DOI: 10.4108/eai.23-11-2023.2343188
Abstract
The traditional method of visually inspecting each lemon and sorting them according to their quality has been done by human inspections. Human inspections can result in some misconceptions while grading the quality of lemons. Lemons are important crops that has many health benefits and plays an important role in the daily lives of poor to rich people. It is not only considered as an important crop within India but all over the globe. It is an essential ingredient in a variety of applications like food industries, medicines, cosmetics etc.,Hence identifying the quality of lemons plays a vital role results in ensuring that the beneficiaries are getting the good quality lemons. The role of deep learning algorithms is high in classification of the lemons based on its quality parameters. The CNN algorithm has been proven the better method when compared with the traditional machine learning algorithms like Suppeor Vector Machine(SVM) and Random Forest. The CNN model proved its accuracy to be 98.75% , which is better results when compared with the traditional methods. This research has proved that the deep learning algorithms are efficient in grading the lemon based on quality parameters.