This work applied remote sensing techniques based on unmanned aerial vehicles (UAVs) and deep learning (DL) to detect WLD in sugarcane fields at the Gal-Oya Plantation, Sri Lanka. The established
methodology to detect WLD consists of UAV red, green, and blue (RGB) image acquisition, the
pre-processing of the dataset, labelling, DL model tuning, and prediction.

Acknowledgements:

• Narmilan Amarasingam conducted the UAV flight mission, and analysis and prepared the manuscript for final submission as a corresponding author.
• Felipe Gonzalez, Kevin Powell, and Juan Sandino provided overall supervision and contributed to the writing and editing.
• Surantha provided the technical guidance to conduct the UAV flight mission and research design and provided feedback on the draft manuscript.