Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery
作者：
Highlights：
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• The problem of remote weed mapping via machine learning is considered.
• Unmanned aerial vehicles are used to capture maize and sunflower field images.
• The proposed method considers pattern and feature selection techniques.
• The final model requires few user information to generalise to new areas.
• There are features of great influence for the classification of both crops.
摘要
•The problem of remote weed mapping via machine learning is considered.•Unmanned aerial vehicles are used to capture maize and sunflower field images.•The proposed method considers pattern and feature selection techniques.•The final model requires few user information to generalise to new areas.•There are features of great influence for the classification of both crops.
论文关键词：Remote sensing,Unmanned aerial vehicles (UAV),Weed detection,Object based image analysis
论文评审过程：Received 7 September 2015, Revised 28 October 2015, Accepted 29 October 2015, Available online 21 November 2015, Version of Record 7 December 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.10.043
