- Communications Faculty of Sciences University Ankara Series A2-A3 Physical and Engineering
- Cilt: 65 Sayı: 2
- Disease detection in bean leaves using deep learning
Disease detection in bean leaves using deep learning
Authors : Soydan Serttaş, Emine Deniz
Pages : 115-129
Doi:10.33769/aupse.1247233
View : 186 | Download : 261
Publication Date : 2023-12-29
Article Type : Research
Abstract :The care and health of agricultural plants, which are the primary source for people to eat healthily, are essential. Disease detection in plants is one of the critical elements of smart agriculture. In parallel with the development of artificial intelligence, advancements in smart agriculture are also progressing. The development of deep learning techniques positively affects smart farming practices. Today, using deep learning and computer vision techniques, various plant diseases can be detected from images such as photographs. In this research, deep learning techniques were used to detect and diagnose bean leaf diseases. Healthy and diseased bean leaf images were used to train the convolutional neural network (CNN) model, which is one of the deep learning techniques. Transfer learning was applied to CNN models to detect plant diseases with the difference of related works. A transfer learning-based strategy to identify various diseases in plant varieties is demonstrated using leaf images of healthy and diseased plants from the Bean dataset. With the proposed method, 1295 images were studied. The results show that our technique successfully identified disease status in bean leaf images, achieving an accuracy of 98.33% with the ResNet50 model.Keywords : Deep learning, bean leaf diseases, image processing, convolutional neural networks