UAV-based high throughput phenotyping in citrus utilizing multispectral imaging and artificial intelligence

Remote Sensing

Volumn 11, Issue 4, 2019, Pages

  Ampatzidis, Yiannis ^a   Partel, Victor ^a  

^a UNIVERSITY OF FLORIDA   (United States)

Author keywords

Artificial intelligence; Deep learning; Machine learning; Neural networks; Precision agriculture; Smart agriculture; UAV

Indexed keywords

ANTENNAS; ARTIFICIAL INTELLIGENCE; COST EFFECTIVENESS; DATA ACQUISITION; FORESTRY; IMAGE PROCESSING; LEARNING SYSTEMS; MACHINE LEARNING; NEURAL NETWORKS; PRECISION AGRICULTURE; REMOTE SENSING; THROUGHPUT; UNMANNED AERIAL VEHICLES (UAV);

CONVOLUTIONAL NEURAL NETWORK; EVALUATION METHODS; HIGH-THROUGHPUT PHENOTYPING; MULTISPECTRAL IMAGING; OVERALL ACCURACIES; PRECISION AND RECALL; REMOTE SENSING TECHNIQUES; SMART AGRICULTURES;

DEEP LEARNING;

EID: 85062501961     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs11040410     Document Type: Article

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