Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015

Volumn , Issue , 2015, Pages 1420-1426

  Puig, E ^a   Gonzalez, F ^a   Hamilton, G ^a   Grundy, P ^b  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^b DEPARTMENT OF AGRICULTURE AND FISHERIES   (Australia)

Author keywords

Biosecurity; K means; Machine learning; Remote sensing; Unmanned aerial vehicles (UAV)

Indexed keywords

ANTENNAS; CROPS; DAMAGE DETECTION; IMAGE PROCESSING; LEARNING SYSTEMS; MACHINE LEARNING; OPERATIONS RESEARCH; REMOTE SENSING; SOILS; SPACE OPTICS; UNMANNED AERIAL VEHICLES (UAV);

BIO-SECURITY; HIGH FREQUENCY COMPONENTS; IMAGE PROCESSING PIPELINE; K-MEANS; MACHINE LEARNING APPROACHES; MACHINE LEARNING TECHNIQUES; SUPERVISED LEARNING APPROACHES; UNSUPERVISED MACHINE LEARNING;

K-MEANS CLUSTERING;

EID: 85075098372     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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