Towards autonomous phytopathology: Outcomes and challenges of citrus greening disease detection through close-range remote sensing

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2016-June, Issue , 2016, Pages 5143-5148

  Sarkar, Suproteem K ^a   Das, Jnaneshwar ^a   Ehsani, Reza ^b   Kumar, Vijay ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CRASHWORTHINESS; LEARNING SYSTEMS; PLANTS (BOTANY); REMOTE SENSING; UNMANNED AERIAL VEHICLES (UAV);

CITRUS GREENING DISEASE; CITRUS PRODUCTION; DEPTH INFORMATION; MACHINE LEARNING MODELS; MOUNTED SENSORS; PLANT PATHOLOGY; SENSING SYSTEMS; STARCH ACCUMULATION;

ROBOTICS;

EID: 84977488477     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICRA.2016.7487719     Document Type: Conference Paper

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