{
  "abstract": "Real-time detection and localization of non-emerged seedlings play a pivotal role in effective vegetable crop management. Traditionally, checking the non-emergence of crop seedlings relies on labor-intensive and time-consuming manual inspections. To address this issue, this paper introduces a precise, rapid, and real-time method for detecting and locating non-emerged seedlings using an unmanned aerial vehicle (UAV). The proposed Enhanced YOLOv8n detector improves upon the base model through a more efficient backbone and a bidirectional feature-fusion neck, achieving a mAP50–95 of 81.4%, an 8% improvement over the base model, while preserving real-time inference capability. Furthermore, integrating the Enhanced YOLOv8n, the YOLO tracking algorithm, and image processing algorithms enabled the development of a robust real-time detection and localization method for non-emerged seedlings. The recognition accuracy for non-emerged cabbage seedlings reached 96.9%. Notably, this method can distinguish the quantity of consecutive non-emerged seedlings, demanding only one-fifth of the manual effort, demonstrating substantial potential for practical applications. In summary, the UAV-deployed real-time detection and localization method exhibits excellent capability in detecting and locating non-emerged cabbage seedlings, thus significantly reducing the manpower needed for crop management.",
  "abstract_shown": true,
  "affiliations": [
    "School of Mechanical Engineering, Nanjing University of Science and Technology",
    "National Engineering Research Center of Biomaterials, Nanjing Forestry University",
    "Shandong Laboratory of Advanced Agricultural Sciences, Peking University Institute of Advanced Agricultural Sciences",
    "Department of Crop, Soil and Environmental Sciences, Auburn University"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Xin Chen"
    },
    {
      "affs": [
        1
      ],
      "name": "Kang Han"
    },
    {
      "affs": [
        2
      ],
      "name": "Teng Liu"
    },
    {
      "affs": [
        2
      ],
      "name": "Xiaotong Kong"
    },
    {
      "affs": [
        3
      ],
      "name": "Aniruddha Maity"
    },
    {
      "affs": [
        0
      ],
      "name": "Peng Peng"
    },
    {
      "affs": [
        0
      ],
      "name": "Changan Di"
    },
    {
      "affs": [
        2
      ],
      "name": "Jialin Yu"
    },
    {
      "affs": [
        1
      ],
      "name": "Maolin Yu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/41qz6e304eddy.bib",
  "cited_by": 0,
  "doi": "10.3389/fpls.2026.1984989",
  "fulltext_url": null,
  "id": "41qz6e304eddy",
  "issns": [
    "1664-462X"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fpls.2026.1984989/full",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1110|Smart Agriculture and AI"
    ]
  ],
  "openalex": "W7224078529",
  "pdf_url": "https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2026.1984989/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-28",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/41qz6e304eddy.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:25Z",
      "native_id": "10.3389/fpls.2026.1984989",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fpls.2026.1984989/full"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:1110|Smart Agriculture and AI",
      "subfield": "plant-biology"
    }
  ],
  "title": "A real-time deep learning method for detection and localization of non-emerged cabbage seedlings",
  "title_text": "A real-time deep learning method for detection and localization of non-emerged cabbage seedlings",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:25Z",
  "url": "https://research.draconitic.com/paper/41qz6e304eddy",
  "venue": "Frontiers in Plant Science",
  "versions": []
}