Classification and Analysis of Tomato Species with Convolutional Neural Networks

Yavuz Selim Taşpınar

Classification and Analysis of Tomato Species with Convolutional Neural Networks

Öz

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.

Anahtar Kelimeler

Ayrıntılar

Birincil Dil

İngilizce

Konular

Ziraat Mühendisliği, Bahçe Bitkileri Yetiştirme ve Islahı

Bölüm

Araştırma Makalesi

Yazarlar

Yavuz Selim Taşpınar Bu kişi benim
Türkiye

Yayımlanma Tarihi

25 Aralık 2022

Gönderilme Tarihi

16 Kasım 2022

Kabul Tarihi

19 Aralık 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: 36 Sayı: 3

IZ

https://izlik.org/JA68JU75FY

Kaynak Göster

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 (01 Aralık 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, c. 36, sy 3, ss. 515–520, Ara. 2022, [çevrimiçi]. Erişim adresi: 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 (01 Aralık 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, c. 36, sy 3, Aralık 2022, ss. 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]. 01 Aralık 2022;36(3):515-20. Erişim adresi: https://izlik.org/JA68JU75FY