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Weed detection and classification for autonomous farming

Abstract

Autonomous weed control concepts have recently being extensively researched due to the advantages that they possess. One of the critical modules of such systems is the sensing and classification of weeds within crops. In this paper, we systematically chose the sensing setup and cues to be used for classification of two common weed species (Bidens pilosa L. and Lolium rigidum L.) in a wheat crop. An automatic cue selection followed by classification procedure is proposed. Some classification results are presented while discussing problems leading to future direction of research

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