{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T15:10:14Z","timestamp":1777043414831,"version":"3.51.4"},"reference-count":45,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T00:00:00Z","timestamp":1740700800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Foundation of the Qingdao Key Laboratory of Groundwater Resources Protection and Rehabilitation","award":["DXSKF2022Y02"],"award-info":[{"award-number":["DXSKF2022Y02"]}]},{"name":"Open Foundation of the Qingdao Key Laboratory of Groundwater Resources Protection and Rehabilitation","award":["801KF2024-DZ07"],"award-info":[{"award-number":["801KF2024-DZ07"]}]},{"name":"Open Foundation of the Qingdao Key Laboratory of Groundwater Resources Protection and Rehabilitation","award":["2024KFKT017"],"award-info":[{"award-number":["2024KFKT017"]}]},{"name":"Open Foundation of the Qingdao Key Laboratory of Groundwater Resources Protection and Rehabilitation","award":["MTY202307"],"award-info":[{"award-number":["MTY202307"]}]},{"name":"Open Foundation of Key Laboratory of Geological Disaster Risk Prevention and Control of Shandong Provincial Emergency Management Department","award":["DXSKF2022Y02"],"award-info":[{"award-number":["DXSKF2022Y02"]}]},{"name":"Open Foundation of Key Laboratory of Geological Disaster Risk Prevention and Control of Shandong Provincial Emergency Management Department","award":["801KF2024-DZ07"],"award-info":[{"award-number":["801KF2024-DZ07"]}]},{"name":"Open Foundation of Key Laboratory of Geological Disaster Risk Prevention and Control of Shandong Provincial Emergency Management Department","award":["2024KFKT017"],"award-info":[{"award-number":["2024KFKT017"]}]},{"name":"Open Foundation of Key Laboratory of Geological Disaster Risk Prevention and Control of Shandong Provincial Emergency Management Department","award":["MTY202307"],"award-info":[{"award-number":["MTY202307"]}]},{"name":"Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements","award":["DXSKF2022Y02"],"award-info":[{"award-number":["DXSKF2022Y02"]}]},{"name":"Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements","award":["801KF2024-DZ07"],"award-info":[{"award-number":["801KF2024-DZ07"]}]},{"name":"Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements","award":["2024KFKT017"],"award-info":[{"award-number":["2024KFKT017"]}]},{"name":"Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements","award":["MTY202307"],"award-info":[{"award-number":["MTY202307"]}]},{"name":"Open Research Fund Program of Anhui Provincial Institute of Modern Coal Processing Technology, Anhui University of Science and Technology","award":["DXSKF2022Y02"],"award-info":[{"award-number":["DXSKF2022Y02"]}]},{"name":"Open Research Fund Program of Anhui Provincial Institute of Modern Coal Processing Technology, Anhui University of Science and Technology","award":["801KF2024-DZ07"],"award-info":[{"award-number":["801KF2024-DZ07"]}]},{"name":"Open Research Fund Program of Anhui Provincial Institute of Modern Coal Processing Technology, Anhui University of Science and Technology","award":["2024KFKT017"],"award-info":[{"award-number":["2024KFKT017"]}]},{"name":"Open Research Fund Program of Anhui Provincial Institute of Modern Coal Processing Technology, Anhui University of Science and Technology","award":["MTY202307"],"award-info":[{"award-number":["MTY202307"]}]},{"name":"Hubei Key Laboratory of Transportation Internet of Things (Wuhan University of Technology)","award":["DXSKF2022Y02"],"award-info":[{"award-number":["DXSKF2022Y02"]}]},{"name":"Hubei Key Laboratory of Transportation Internet of Things (Wuhan University of Technology)","award":["801KF2024-DZ07"],"award-info":[{"award-number":["801KF2024-DZ07"]}]},{"name":"Hubei Key Laboratory of Transportation Internet of Things (Wuhan University of Technology)","award":["2024KFKT017"],"award-info":[{"award-number":["2024KFKT017"]}]},{"name":"Hubei Key Laboratory of Transportation Internet of Things (Wuhan University of Technology)","award":["MTY202307"],"award-info":[{"award-number":["MTY202307"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Lilies, a key cash crop in Lanzhou, China, widely planted in coal-based fields, cultivated fields, and gardens, face significant yield and quality reduction due to weed infestation, which competes for essential nutrients, water, and light. To address this challenge, we propose an advanced weed detection method that combines symmetry-based convolutional neural networks with metaheuristic optimization. A dedicated weed detection dataset is constructed through extensive field investigation, data collection, and annotation. To enhance detection efficiency, we introduce an optimized YOLOv7-Tiny model, integrating dynamic pruning and knowledge distillation, which reduces computational complexity while maintaining high accuracy. Additionally, a novel Chaotic Harris Hawks Optimization (CHHO) algorithm, incorporating chaotic mapping initialization and differential evolution, is developed to fine-tune YOLOv7-Tiny parameters and activation functions. Experimental results demonstrate that the optimized YOLOv7-Tiny achieves a detection accuracy of 92.53% outperforming traditional models while maintaining efficiency. This study provides a high-performance, lightweight, and scalable solution for real-time precision weed management in lily fields, offering valuable insights for agricultural automation and smart farming applications.<\/jats:p>","DOI":"10.3390\/sym17030370","type":"journal-article","created":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T10:12:33Z","timestamp":1740737553000},"page":"370","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Weed Detection in Lily Fields Using YOLOv7 Optimized by Chaotic Harris Hawks Algorithm for Underground Resource Competition"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2695-6484","authenticated-orcid":false,"given":"Junjie","family":"Tang","sequence":"first","affiliation":[{"name":"Anhui Provincial Institute of Modern Coal Processing Technology, Anhui University of Science and Technology, Huainan 232001, China"},{"name":"School of Electronic Information Engineering, Southwest University, Chongqing 400715, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huafei","family":"Wang","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingyue","family":"Zhao","sequence":"additional","affiliation":[{"name":"Qingdao Key Laboratory of Groundwater Resources Protection and Rehabilitation, Qingdao Geo-Engineering Surveying Institute, Qingdao 266101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Sun","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geological Safety of Coastal Urban Underground Space, Ministry of Natural Resources, Qingdao 266101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yutao","family":"Hao","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Southwest University, Chongqing 400715, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyuan","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Southwest University, Chongqing 400715, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, X., Xue, L., Wu, Z., Zhang, W., Zhang, H., Zhao, C., and Liu, D. 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