{
  "abstract": "This work presents an engineering-oriented data processing and model training pipeline for EAST visible and WEST infrared data, enabling a systematic study of cross-device and cross-modal electric arc detection. A lightweight convolutional neural network is adopted as a cross-device arc detection model, and joint training and transfer learning experiments are conducted on EAST visible (VIS) and WEST infrared (IR) data. Single-modality baselines are first trained on EAST and WEST, then evaluated zero-shot on the opposite device, followed by a comparison of frozen-backbone and fine-tuned transfer for VIS→IR and IR→VIS.The results show that models trained from scratch on each diagnostic channel already achieve high precision and recall for arc detection, whereas direct zero-shot cross-modal transfer drives the arc recall on the opposite domain almost to zero. In contrast, starting from the single-modality baselines and modestly fine tuning higher convolutional layers and the classification head on the target domain can significantly restore-cross device, cross-modal detection performance, with positive class precision and recall approaching or even surpassing the single-domain baselines. Class activation map analysis further indicates that, under fine-tuned and joint training configurations, the models consistently focus on the antenna, the arc, and its surrounding scattering region, supporting physically meaningful explanations and suggesting that cross-device, cross-modal training can capture arc related structures that generalize across devices while providing a lightweight, scalable route to reusing imaging-based diagnostic",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 28,
  "authors": [
    {
      "name": "Zhongfang Guan"
    },
    {
      "name": "Erwan Grelier"
    },
    {
      "name": "Bin Zhang"
    },
    {
      "name": "Sébastien Vives"
    },
    {
      "name": "Baoguo Wang"
    },
    {
      "name": "Victor Moncada"
    },
    {
      "name": "Leo Dubus"
    },
    {
      "name": "Jinping Qian"
    },
    {
      "name": "Kedong Li"
    },
    {
      "name": "Jian Liu"
    },
    {
      "name": "Cong Cao"
    },
    {
      "name": "Zuhao Wang"
    },
    {
      "name": "Binfu Gao"
    },
    {
      "name": "Chuannan Xuan"
    },
    {
      "name": "Yang Wang"
    },
    {
      "name": "Xiaoming Zhong"
    },
    {
      "name": "Runze Chen"
    },
    {
      "name": "Yutong Guo"
    },
    {
      "name": "Qian Wang"
    },
    {
      "name": "Tianqi Jia"
    },
    {
      "name": "Pan Li"
    },
    {
      "name": "Wenbin Liu"
    },
    {
      "name": "Xiushuo Zhang"
    },
    {
      "name": "Yunchan Hu"
    },
    {
      "name": "Yifan He"
    },
    {
      "name": "Wenyi Lu"
    },
    {
      "name": "Chun Yu He"
    },
    {
      "name": "Xianzu Gong"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3b6afwg1r1hak.bib",
  "cited_by": 0,
  "doi": "10.1088/1741-4326/aeb036",
  "fulltext_url": null,
  "id": "3b6afwg1r1hak",
  "issns": [
    "0029-5515",
    "1741-4326"
  ],
  "landing_url": "https://cea.hal.science/cea-05787077v1",
  "language": "en",
  "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": [
    [
      "hal",
      "0.info"
    ],
    [
      "hal",
      "0.phys"
    ],
    [
      "hal",
      "1.info.info-ai"
    ],
    [
      "hal",
      "1.info.info-cv"
    ],
    [
      "hal",
      "1.phys.nexp"
    ],
    [
      "openalex",
      "1702|Domain Adaptation and Few-Shot Learning"
    ]
  ],
  "openalex": "W7220459014",
  "pdf_url": "https://cea.hal.science/cea-05787077/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-05",
  "publisher": "IOP Publishing",
  "ris": "https://research.draconitic.com/paper/3b6afwg1r1hak.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:51Z",
      "native_id": "cea-05787077",
      "source": "hal",
      "url": "https://cea.hal.science/cea-05787077v1"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "hal:1.phys.nexp",
      "subfield": "nuclear"
    }
  ],
  "title": "Cross‑device and cross‑modal arc detection: Transfer learning between EAST visible and WEST infrared diagnostics",
  "title_text": "Cross‑device and cross‑modal arc detection: Transfer learning between EAST visible and WEST infrared diagnostics",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:51Z",
  "url": "https://research.draconitic.com/paper/3b6afwg1r1hak",
  "venue": "Nuclear Fusion",
  "versions": []
}