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Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery

(2018) BIOSYSTEMS ENGINEERING. 170. p.39-50
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Keywords
Snapshot hyperspectral imaging, Machine learning, Plant classification, Hyperparameter tuning, Feature selection, Cross validation

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Citation

Please use this url to cite or link to this publication:

Chicago
Gao, Junfeng, David Nuyttens, Peter Lootens, Yong He, and Jan Pieters. 2018. “Recognising Weeds in a Maize Crop Using a Random Forest Machine-learning Algorithm and Near-infrared Snapshot Mosaic Hyperspectral Imagery.” Biosystems Engineering 170: 39–50.
APA
Gao, Junfeng, Nuyttens, D., Lootens, P., He, Y., & Pieters, J. (2018). Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery. BIOSYSTEMS ENGINEERING, 170, 39–50.
Vancouver
1.
Gao J, Nuyttens D, Lootens P, He Y, Pieters J. Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery. BIOSYSTEMS ENGINEERING. 2018;170:39–50.
MLA
Gao, Junfeng, David Nuyttens, Peter Lootens, et al. “Recognising Weeds in a Maize Crop Using a Random Forest Machine-learning Algorithm and Near-infrared Snapshot Mosaic Hyperspectral Imagery.” BIOSYSTEMS ENGINEERING 170 (2018): 39–50. Print.
@article{8557865,
  author       = {Gao, Junfeng and Nuyttens, David and Lootens, Peter and He, Yong and Pieters, Jan},
  issn         = {1537-5110},
  journal      = {BIOSYSTEMS ENGINEERING},
  keyword      = {Snapshot hyperspectral imaging,Machine learning,Plant classification,Hyperparameter tuning,Feature selection,Cross validation},
  language     = {eng},
  pages        = {39--50},
  title        = {Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral~imagery},
  url          = {http://dx.doi.org/10.1016/j.biosystemseng.2018.03.006},
  volume       = {170},
  year         = {2018},
}

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