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Open AccessArticle

Apple Leaf Diseases Recognition Based on An Improved Convolutional Neural Network

by 1,2,†, 3,†, 1, 1,2,*, 4 and 4
1
School of Electrical and Information Engineering, Anhui University of Technology, Ma’anshan 243032, China
2
Key Laboratory of Power Electronics and Motion Control Anhui Education Department, Anhui University of Technology, Ma’anshan 243032, China
3
School of Information and Computer, Anhui Agricultural University, Hefei 230036, China
4
Co-Innovation Center for Information Supply & Assurance Technology, Anhui University, Hefei 230032, China
*
Author to whom correspondence should be addressed.
These authors are equally contributed to this work.
Sensors 2020, 20(12), 3535; https://doi.org/10.3390/s20123535
Received: 6 April 2020 / Revised: 12 June 2020 / Accepted: 17 June 2020 / Published: 22 June 2020
Scab, frogeye spot, and cedar rust are three common types of apple leaf diseases, and the rapid diagnosis and accurate identification of them play an important role in the development of apple production. In this work, an improved model based on VGG16 is proposed to identify apple leaf diseases, in which the global average poling layer is used to replace the fully connected layer to reduce the parameters and a batch normalization layer is added to improve the convergence speed. A transfer learning strategy is used to avoid a long training time. The experimental results show that the overall accuracy of apple leaf classification based on the proposed model can reach 99.01%. Compared with the classical VGG16, the model parameters are reduced by 89%, the recognition accuracy is improved by 6.3%, and the training time is reduced to 0.56% of that of the original model. Therefore, the deep convolutional neural network model proposed in this work provides a better solution for the identification of apple leaf diseases with higher accuracy and a faster convergence speed. View Full-Text
Keywords: apple leaf diseases; transfer learning; deep learning; convolutional neural networks apple leaf diseases; transfer learning; deep learning; convolutional neural networks
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MDPI and ACS Style

Yan, Q.; Yang, B.; Wang, W.; Wang, B.; Chen, P.; Zhang, J. Apple Leaf Diseases Recognition Based on An Improved Convolutional Neural Network. Sensors 2020, 20, 3535. https://doi.org/10.3390/s20123535

AMA Style

Yan Q, Yang B, Wang W, Wang B, Chen P, Zhang J. Apple Leaf Diseases Recognition Based on An Improved Convolutional Neural Network. Sensors. 2020; 20(12):3535. https://doi.org/10.3390/s20123535

Chicago/Turabian Style

Yan, Qian; Yang, Baohua; Wang, Wenyan; Wang, Bing; Chen, Peng; Zhang, Jun. 2020. "Apple Leaf Diseases Recognition Based on An Improved Convolutional Neural Network" Sensors 20, no. 12: 3535. https://doi.org/10.3390/s20123535

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