Balkan Journal of Electrical and Computer Engineering

2147-284X 2147-284X

MUSA YILMAZ

10.17694/bajece.1335257

Electrical Engineering (Other)

Elektrik Mühendisliği (Diğer)

Detection of Various Diseases in Fruits and Vegetables with the Help of Different Deep Learning Techniques

https://orcid.org/0009-0007-2194-8561

Özcan

Sevil

BATMAN UNIVERSITY, INSTITUTE OF SCIENCE

https://orcid.org/0000-0002-1897-9830

Acar

Emrullah

BATMAN ÜNİVERSİTESİ

03 01 2024

12 1 62 67 07 31 2023 12 11 2023

2013

Balkan Journal of Electrical and Computer Engineering

Fruit and vegetable diseases have an important place in the food sector in terms of sustainable agricultural policies. Thus, ıt affects tissues, targeting and negatively impacting the food supply. In this study, Two separate Deep Learning (CNN, AlexNet) models were employed to detect this difference, visual damage and surface marker seen in fruits and vegetables. 22 strawberries and 18 tomato images were used for this analysis, and than data augmentation was implemented 600 images out of 40 images using the image reproduction broadcast. As a result, 83.3% success was achieved.

Deep learning convolutıonal neural network (cnn) fruit and vegetable disease

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