Real-Time Identification of Rice Weeds by UAV Low-Altitude Remote Sensing Based on Improved Semantic Segmentation Model

Real-time analysis of UAV low-altitude remote sensing images at airborne terminals facilitates the timely monitoring of weeds in the farmland. Aiming at the real-time identification of rice weeds by UAV low-altitude remote sensing, two improved identification models, MobileNetV2-UNet and FFB-BiSeNet...

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Autores principales:	Yubin Lan, Kanghua Huang, Chang Yang, Luocheng Lei, Jiahang Ye, Jianling Zhang, Wen Zeng, Yali Zhang, Jizhong Deng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	low-altitude remote sensing semantic segmentation model real-time rice weeds target spraying Science Q
Acceso en línea:	https://doaj.org/article/3545b7338c78431a8b9dc465e394d63c
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Real-Time Identification of Rice Weeds by UAV Low-Altitude Remote Sensing Based on Improved Semantic Segmentation Model

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