DCNN Transfer Learning and Multi-model Integration for Disease and Weed Identification-Reference-Cited by-同舟云学术

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DCNN Transfer Learning and Multi-model Integration for Disease and Weed Identification

Published:2019 Issue: Volume: Page:216-227
ISSN:1865-0929
Container-title:Image and Graphics Technologies and Applications
language:
Short-container-title:

Author:

Wang Jingxian,Li Miao,Zhang Jian,Zeng WeiHui,Yang XuanJiang

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-13-9917-6_21

Reference18 articles.

1. Li, J., Gao, L., Shen, Z.: Extraction and analysis of digital images feature of three kinds of wheat diseases. In: International Congress on Image and Signal Processing (2010)

2. Meyer, G.E., Neto, J.C., Jones, D.D., Hindman, T.W.: Intensified fuzzy clusters for classifying plant, soil, and residue regions of interest from color images. Comput. Electron. Agric. 42(3), 161–180 (2004)

3. Nachtigall, L.G., Araujo, R.M., Nachtigall, G.R.: Classification of apple tree disorders using convolutional neural networks. In: IEEE International Conference on Tools with Artificial Intelligence (2017)

4. Lecture Notes in Computer Science;Y Kawasaki,2015

5. Jiang, L., Jie, H., Zhao, G., Mei, F., Zhang, C.: An in-field automatic wheat disease diagnosis system. Comput. Electron. Agric. 142, 369–379 (2017)

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