Segmenting Crop Disease Leaf Image by Modified Fully-Convolutional Networks-Reference-Cited by-同舟云学术

Segmenting Crop Disease Leaf Image by Modified Fully-Convolutional Networks

Published:2019 Issue: Volume: Page:646-652
ISSN:0302-9743
Container-title:Intelligent Computing Theories and Application
language:
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Author:

Wang Xian-feng,Wang Zhen,Zhang Shan-wen

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-26763-6_62

Reference24 articles.

1. Martinelli, F., Scalenghe, R., Davino, S., et al.: Advanced methods of plant disease detection. A review. Agron. Sustain. Dev. 35(1), 1–25 (2015)

2. Shelhamer, E., Long, J., Darrell, T.: Fully convolutional networks for semantic segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 1 (2016). https://doi.org/10.1109/tpami.2016.2572683

3. Du, M.G., Zhang, S.W.: Crop disease leaf image segmentation based on genetic algorithm and maximum entropy. Appl. Mech. Mater. 713–715 (2015)

4. Wang, L., Tao, Y., Tian, Y.: Crop disease leaf image segmentation method based on color features. In: International Conference on Computer & Computing Technologies in Agriculture, pp. 713–717 (2007)

5. Guan, H.O., Shao-Hua, X.U., Feng, T.: Fuzzy neural network based on T-S model and its application on image segmentation of plant diseases. J. China Agric. Univ. 16(3), 145–149 (2011)

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