@inproceedings{2fecda81d57b43f1bd4dee3d90a54006,
title = "Crop disease image classification based on transfer learning with DCNNs",
abstract = "Machine learning has been widely used in the crop disease image classification. Traditional methods relying on the extraction of hand-crafted low-level image features are difficulty to get satisfactory results. Deep convolutional neural network can deal with this problem because of automatically learning the feature representations from raw image data, but require enough labeled data to obtain a good generalization performance. However, in the field of agriculture, the available labeled data in target task is limited. In order to solve this problem, this paper proposes a method which combines transfer learning with two popular deep learning architectures (i.e., AlexNet and VGGNet) to classify eight kinds of crop diseases images. First, during the training procedure, the batch normalization and DisturbLabel techniques are introduced into these two networks to reduce the number of training iterations and over-fitting. Then, after training the pre-trained model by using the open source dataset PlantVillage. Finally, we fine-tune this model with our relatively small dataset preprocessed by a proposed strategy. The experimental results reveal that our approach can achieve an average accuracy of 95.93% compared to state-of-the-art method for our relatively small dataset, demonstrating the feasibility and robustness of this approach.",
keywords = "Crop diseases, DCNN, Deep learning, Image classification, Transfer learning",
author = "Yuan Yuan and Sisi Fang and Lei Chen",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 1st Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018 ; Conference date: 23-11-2018 Through 26-11-2018",
year = "2018",
doi = "10.1007/978-3-030-03335-4_40",
language = "英语",
isbn = "9783030033347",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "457--468",
editor = "Cheng-Lin Liu and Tieniu Tan and Jie Zhou and Jian-Huang Lai and Xilin Chen and Nanning Zheng and Hongbin Zha",
booktitle = "Pattern Recognition and Computer Vision - First Chinese Conference, PRCV 2018, Proceedings",
}