Crop disease image classification based on transfer learning with DCNNs

Yuan Yuan, Sisi Fang, Lei Chen

科研成果: 书/报告/会议事项章节会议稿件同行评审

20 引用 (Scopus)

摘要

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.

源语言英语
主期刊名Pattern Recognition and Computer Vision - First Chinese Conference, PRCV 2018, Proceedings
编辑Cheng-Lin Liu, Tieniu Tan, Jie Zhou, Jian-Huang Lai, Xilin Chen, Nanning Zheng, Hongbin Zha
出版商Springer Verlag
457-468
页数12
ISBN(印刷版)9783030033347
DOI
出版状态已出版 - 2018
已对外发布
活动1st Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018 - Guangzhou, 中国
期限: 23 11月 201826 11月 2018

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11257 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议1st Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018
国家/地区中国
Guangzhou
时期23/11/1826/11/18

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