Healthy and Diseased Tomatoes Detection Based on YOLOv2-Reference-Cited by-同舟云学术

Healthy and Diseased Tomatoes Detection Based on YOLOv2

Published:2019 Issue: Volume: Page:347-353
ISSN:0302-9743
Container-title:Human Centered Computing
language:
Short-container-title:

Author:

Zhao Jiayue^ORCID,Qu Jianhua

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-15127-0_34

Reference16 articles.

1. Huang, Z.H.: Research on construction method of Tomato Disease Image Database. South China Agricultural University (2016)

2. Zhou, Y.C., Xu, T.Y., Zheng, W., Deng, H.B.: Classification and recognition approaches of tomato main organs based on DCNN. Trans. Chin. Soc. Agric. Eng. 33(15), 219–226 (2017)

3. Zhou, Y.C., Xu, T.Y., Deng, H.B., Miao, T.: Recognition method of tomato key organs based on dual convolution Fast R-CNN. J. Shenyang Agric. Univ. 49(01), 65–74 (2018)

4. Zhou, Y.C., Xu, T.Y., Deng, H.B., Miao, T.: Real-time recognition of main organs in tomato based on channel wise group convolutional network. Trans. Chin. Soc. Agric. Eng. 34(10), 153–162 (2018)

5. Fang, J.L., Zhang, C.L., Pan, W., Wang, S.W.: Automated identification of tomatoes with diseases using artificial neural network trained with genetic algorithms. Trans. Chin. Soc. Agric. Eng. 03, 113–116 (2004)

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