2024
DOI: 10.20944/preprints202405.0018.v1
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Improved YOLOv8-seg Based on Multi-scale Feature Fusion and Deformable Convolution for Weed Precision Segmentation

Zhuxi Lyu,
Anjiang Lu,
Yinglong Ma

Abstract: Laser-targeted weeding methods further enhance the sustainable development of green agriculture, with one key technology being the improvement of weed localization accuracy. Here, we propose an improved YOLOv8 instance segmentation based on bidirectional feature fusion and deformable convolution (BFFDC-YOLOv8-seg) to address the challenges of insufficient weed localization accuracy in complex environments with resource-limited laser weeding devices. Initially, by training on extensive datasets of plant images,… Show more

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