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Identification of rice diseases using deep convolutional neural networks

Neurocomputing · 2017 · Vol. 267 · pp. 378–384
Yang LüShujuan YiNianyin ZengYurong LiuYong Zhang
Smart Agriculture and AISpectroscopy and Chemometric AnalysesGenetic Mapping and Diversity in Plants and AnimalsConvolutional neural networkArtificial intelligenceIdentification (biology)Deep learningComputer scienceField (mathematics)Rice plantPattern recognition (psychology)Paddy fieldMachine learning

Funding

  • National Natural Science Foundation of China
  • China Postdoctoral Science Foundation
  • Natural Science Foundation of Heilongjiang Province
  • Heilongjiang Bayi Agricultural University
Citations
1,009
FWCI
103.40
field-weighted impact
References
42
Percentile
100%
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Citations per year
References
Gradient-based learning applied to document recognition
Proceedings of the IEEE · 1998 · 57,014 citations
ImageNet Large Scale Visual Recognition Challenge
International Journal of Computer Vision · 2015 · 39,683 citations
ImageNet classification with deep convolutional neural networks
Communications of the ACM · 2017 · 75,550 citations
Deep learning
Nature · 2015 · 79,164 citations
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