IMPROVED YOLOV8-SEG BASED ON MULTISCALE FEATURE FUSION AND DEFORMABLE CONVOLUTION FOR WEED PRECISION SEGMENTATION

Improved YOLOv8-Seg Based on Multiscale Feature Fusion and Deformable Convolution for Weed Precision Segmentation

Laser-targeted weeding methods further enhance the sustainable development of Shirt 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

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Microwave assisted synthesis and characterisation of a zinc oxide/tobacco mosaic virus hybrid material. An active hybrid semiconductor in a field-effect transistor device

Tobacco mosaic virus (TMV) has been employed as a robust functional template for the fabrication of a TMV/zinc oxide field effect transistor (FET).A microwave based diegojavierfares.com approach, under mild conditions was employed to synthesize stable zinc oxide (ZnO) nanoparticles, employing a molecular precursor.Insightful studies of the decompos

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