The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Application of distributed SVM architectures in classifying forest data cover types
Computers and Electronics in Agriculture
Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems
Journal of Field Robotics
Aquatic weed automatic classification using machine learning techniques
Computers and Electronics in Agriculture
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This paper addresses the novel application of an autonomous rotary-wing unmanned air vehicle (RUAV) as a cost-effective tool for the surveillance and management of aquatic weeds. A conservative estimate of the annual loss of agricultural revenue to the Australian economy due to weeds is in the order of A$4 billion, hence the reason why weed control is of national significance. The presented system locates and identifies weeds in inaccessible locations. The RUAV is equipped with low-cost sensor suites and various weed detection algorithms. In order to provide the weed control operators with the capability of autonomous or remote control spraying and treatment of the aquatic weeds the RUAV is also fitted with a spray mechanism. The system has been demonstrated over inaccessible weed infested aquatic habitats.