Classification and Analysis of Tomato Species with Convolutional Neural Networks

Yavuz Selim Taşpınar

Classification and Analysis of Tomato Species with Convolutional Neural Networks

Abstract

Tomatoes are one of the most used vegetables. There are varieties that can grow in different climates. The taste, usage area and commercial value of each are different from each other. For this reason, identifying and sorting tomato species after the production stage is a problem. In addition, since tomato is a sensitive vegetable, it is extremely important to separate it from a distance. For this purpose, the classification of tomato images belonging to 9 different tomato species was carried out in the study. In total, a dataset containing 6810 tomato images in 9 classes was used. Three different pre-trained Convolutional Neural Network (CNN) models were used with the transfer learning method to classify the images. AlexNet, InceptionV3 and VGG16 models were used for classification. As a result of the classifications made, the highest classification belongs to the AlexNet model with 100%. Evaluation of the performances of the models was also made with precision, recall, F1 Score and specificity performance metrics. It is foreseen that the proposed methods can be used for the separation of tomatoes.

Keywords

Details

Primary Language

English

Subjects

Agricultural Engineering, Horticultural Production

Journal Section

Research Article

Authors

Yavuz Selim Taşpınar This is me
Türkiye

Publication Date

December 25, 2022

Submission Date

November 16, 2022

Acceptance Date

December 19, 2022

Published in Issue

Year 2022 Volume: 36 Number: 3

IZ

https://izlik.org/JA68JU75FY

Cite

RIS / Bibtex

APA

Taşpınar, Y. S. (2022). Classification and Analysis of Tomato Species with Convolutional Neural Networks. Selcuk Journal of Agriculture and Food Sciences, 36(3), 515-520. https://izlik.org/JA68JU75FY

AMA

1.Taşpınar YS. Classification and Analysis of Tomato Species with Convolutional Neural Networks. Selcuk J Agr Food Sci. 2022;36(3):515-520. https://izlik.org/JA68JU75FY

Chicago

Taşpınar, Yavuz Selim. 2022. “Classification and Analysis of Tomato Species With Convolutional Neural Networks”. Selcuk Journal of Agriculture and Food Sciences 36 (3): 515-20. https://izlik.org/JA68JU75FY.

EndNote

Taşpınar YS (December 1, 2022) Classification and Analysis of Tomato Species with Convolutional Neural Networks. Selcuk Journal of Agriculture and Food Sciences 36 3 515–520.

IEEE

[1]Y. S. Taşpınar, “Classification and Analysis of Tomato Species with Convolutional Neural Networks”, Selcuk J Agr Food Sci, vol. 36, no. 3, pp. 515–520, Dec. 2022, [Online]. Available: https://izlik.org/JA68JU75FY

ISNAD

Taşpınar, Yavuz Selim. “Classification and Analysis of Tomato Species With Convolutional Neural Networks”. Selcuk Journal of Agriculture and Food Sciences 36/3 (December 1, 2022): 515-520. https://izlik.org/JA68JU75FY.

JAMA

1.Taşpınar YS. Classification and Analysis of Tomato Species with Convolutional Neural Networks. Selcuk J Agr Food Sci. 2022;36:515–520.

MLA

Taşpınar, Yavuz Selim. “Classification and Analysis of Tomato Species With Convolutional Neural Networks”. Selcuk Journal of Agriculture and Food Sciences, vol. 36, no. 3, Dec. 2022, pp. 515-20, https://izlik.org/JA68JU75FY.

Vancouver

1.Yavuz Selim Taşpınar. Classification and Analysis of Tomato Species with Convolutional Neural Networks. Selcuk J Agr Food Sci [Internet]. 2022 Dec. 1;36(3):515-20. Available from: https://izlik.org/JA68JU75FY