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Volunteer cotton plant detection in corn field with deep learning

Volunteer cotton (VC) plants growing in fields of inter-seasonal crop like corn can act as host for the boll weevil pests; therefore, they need to be detected, located, and sprayed to prevent reinfestation of the pest in the following season. However, detecting the VC plants in corn fields has always been challenging as they remain hidden under the canopy and appear spectrally similar during the early growth phase. In this paper, we show that deep learning based YOLOv3 model can be used to detect VC plants in early growth corn field on RGB aerial images collected remotely by unmanned aircraft system (UAS) at a mean average precision (mAP) of 90.60% and F1-score of 86.35%. The approach of using deep learning to detect VC plants demonstrates its ability to be used for near real-time detection thereby expediting the management aspects of Texas Boll Weevil Eradication Program.