A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery

PLoS ONE

Volumn 13, Issue 4, 2018, Pages

  Huang, Huasheng ^a,b   Deng, Jizhong ^a,b   Lan, Yubin ^a,b   Yang, Aqing ^a   Deng, Xiaoling ^a,b   Zhang, Lei ^a,b  

^a SOUTH CHINA AGRICULTURAL UNIVERSITY   (China)

^b International Lab of Agricultural Aviation Pesticide Spraying Technology   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CHINA; HUMAN; HUMAN EXPERIMENT; IMAGERY; NONHUMAN; PREDICTION; RICE; TRANSFER OF LEARNING; AGRICULTURE; AIRCRAFT; ALGORITHM; GUIDED IMAGERY; ORYZA; PHYSIOLOGY; PLANT; PROCEDURES; REMOTE SENSING; SOFTWARE; STATISTICAL MODEL; WEED;

AGRICULTURE; AIRCRAFT; ALGORITHMS; CHINA; IMAGERY (PSYCHOTHERAPY); MODELS, STATISTICAL; ORYZA; PLANT WEEDS; PLANTS; REMOTE SENSING TECHNOLOGY; SOFTWARE;

EID: 85046034633     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0196302     Document Type: Article

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