A Semi-Supervised Diffusion-Based Framework for Weed Detection in Precision Agricultural Scenarios Using a Generative Attention Mechanism

A Semi-Supervised Diffusion-Based Framework for Weed Detection in Precision Agricultural Scenarios Using a Generative Attention Mechanism

The development of smart agriculture has created an urgent demand for efficient and accurate weed recognition and detection technologies. However, the diverse and complex morphology of weeds, coupled with the scarcity of labeled data in agricultural scenarios, poses significant challenges to traditi...

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Bibliographic Details
Main Authors: Ruiheng Li, Xuaner Wang, Yuzhuo Cui, Yifei Xu, Yuhao Zhou, Xuechun Tang, Chenlu Jiang, Yihong Song, Hegan Dong, Shuo Yan
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Agriculture
Subjects:
artificial intelligence in agriculture
weed detection
multi-scale feature extraction
deep learning
precision agriculture
Online Access:https://www.mdpi.com/2077-0472/15/4/434
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