Automatic Localization and Count of Agricultural Crop Pests Based on an Improved Deep Learning Pipeline

Author:

Li Weilu,Chen PengORCID,Wang Bing,Xie Chengjun

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference23 articles.

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2. Magarey, R. D. et al. Risk maps for targeting exotic plant pest detection programs in the united states. Eppo Bull. 41, 46–56 (2011).

3. Wang, Y. & Luo, Y. Pest recognition spraying device design based on pc image processing and near infrared spectrum analysis. J. Agric. Mech. Res. (2017).

4. Sethy, P. et al. Pest detection and recognition in rice crop using svm in approach of bag-of-words (2017).

5. Xia, S., Chen, P., Zhang, J., Li, X. & Wang, B. Utilization of rotation-invariant uniform LBP histogram distribution and statistics of connected regions in automatic image annotation based on multi-label learning. Neurocomputing 228, 11–18 (2017).

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