{
  "abstract": "Detecting infrared small targets continues to be difficult because of indistinct object contours, intense background interference, and restricted multi-scale feature extraction. To tackle such problems, this work introduces EDGRU, an edge-oriented dual graph reasoning U-Net which simultaneously utilizes edge information and dual graph logic, and spatial graph attention for robust feature representation. Specifically, a multi-directional multi-order gradient edge module is designed to preserve weak structural details and suppress background interference. A dual graph reasoning framework enhances both local spatial dependencies and long-range semantic relationships, while spatial graph attention further strengthens topology-aware feature interaction to improve target-background discrimination. Empirical evaluations conducted on the NUAA-SIRST and NUDT-SIRST benchmarks reveal that EDGRU achieves the highest detection probability of 96.58% and 98.84%, respectively, while remaining competitive on other metrics, demonstrating enhanced resilience against complex environments and target scale fluctuations. The source code for this project is accessible at https://github.com/Huang-1015/EDGRU.git .",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "Xinying Huang"
    },
    {
      "name": "Jianhua Song"
    },
    {
      "name": "Xinrong Fu"
    },
    {
      "name": "Yizhe Lu"
    },
    {
      "name": "Lei Yuan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dwa7wejqws7mg.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-76517-6",
  "fulltext_url": null,
  "id": "dwa7wejqws7mg",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-76517-6",
  "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",
      "2202|Infrared Target Detection Methodologies"
    ]
  ],
  "openalex": "W7223889769",
  "pdf_url": "https://www.nature.com/articles/s41598-026-76517-6_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-27",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/dwa7wejqws7mg.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:34Z",
      "native_id": "10.1038/s41598-026-76517-6",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-76517-6"
    }
  ],
  "subjects": [],
  "title": "EDGRU: edge-guided dual graph reasoning U-Net with spatial graph attention for infrared small target detection",
  "title_text": "EDGRU: edge-guided dual graph reasoning U-Net with spatial graph attention for infrared small target detection",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:34Z",
  "url": "https://research.draconitic.com/paper/dwa7wejqws7mg",
  "venue": "Scientific Reports",
  "versions": []
}