Research on agricultural smart weeding vehicles with high generalization capability for weed detection
To address the limitations in weed detection and localization capabilities of existing smart weeding machines,we develop a new agricultural smart weeding vehicle with enhanced generalization capabilities for weed detection and localization.Equipped with an image sensor for capturing field weed images,it utilizes a deep learning model for precise weed localization and ensures accurate weeding without harming crops via a servo motor-controlled rotating rake disc.Furthermore,a data augmentation strategy based on generative adversarial networks is implemented,enhancing the generation quality of weed images and the stability of network training.The strategy involves synthesizing new images from field weed images to expand the dataset,improving its comprehensiveness and diversity.Our results show our newly developed smart weeding vehicle not only operates with high efficiency and low crop damage but also boosts the generalization ability of the weed detection system.
国家科技期刊平台
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