{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:44:12Z","timestamp":1760060652005,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T00:00:00Z","timestamp":1757462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62201438","62331019","2024AAC05057","2024AAC02035","2022YFA1604803","2025JC-YBMS-020"],"award-info":[{"award-number":["62201438","62331019","2024AAC05057","2024AAC02035","2022YFA1604803","2025JC-YBMS-020"]}]},{"name":"Natural Science Foundation of Ningxia Province of China","award":["62201438","62331019","2024AAC05057","2024AAC02035","2022YFA1604803","2025JC-YBMS-020"],"award-info":[{"award-number":["62201438","62331019","2024AAC05057","2024AAC02035","2022YFA1604803","2025JC-YBMS-020"]}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["62201438","62331019","2024AAC05057","2024AAC02035","2022YFA1604803","2025JC-YBMS-020"],"award-info":[{"award-number":["62201438","62331019","2024AAC05057","2024AAC02035","2022YFA1604803","2025JC-YBMS-020"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Basic Research Program of Shaanxi","award":["62201438","62331019","2024AAC05057","2024AAC02035","2022YFA1604803","2025JC-YBMS-020"],"award-info":[{"award-number":["62201438","62331019","2024AAC05057","2024AAC02035","2022YFA1604803","2025JC-YBMS-020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Railway service interruptions and electrical hazards often arise due to bird nests concealed within the intricate, highly symmetric overhead catenary networks of high-speed lines. These nests are difficult to pinpoint automatically, not only because they are diminutive and often merge visually with the surroundings but also due to occlusions and the persistent lack of substantial labeled datasets. To address this bottleneck, this work presents the High-Speed Railway Catenary Nest Dataset (HRC-Nest), merging 800 authentic images and 1000 synthetic samples to capture a spectrum of scenarios. Building on the symmetry of catenary structures\u2014where nests appear as localized asymmetries\u2014the Symmetry-Aware Railway Nest Detection Framework (RNDF) is proposed, an enhanced YOLOv12 system for accurate and robust nest detection in symmetric high-speed railway catenary environments. With the A2C2f_HRAMi design, the RNDF learns from multi-level features by unifying residual and hierarchical attention strategies. The SCSA component boosts the recognition in visually cluttered or obstructed settings further by jointly processing spatial and channel-wise signals. To sharpen the detection accuracy, particularly for subtle, hidden nests, the Focaler-GIoU loss guides bounding box optimization. Comparative studies show that the RNDF consistently outperforms recent detectors, surpassing the YOLOv12 baseline by 5.95% mAP@0.5 and 26.16% mAP@0.5:0.95, underscoring its suitability for symmetry-aware, real-world catenary anomaly monitoring.<\/jats:p>","DOI":"10.3390\/sym17091505","type":"journal-article","created":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T12:04:55Z","timestamp":1757505895000},"page":"1505","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Symmetry-Aware Multi-Attention Framework for Bird Nest Detection on Railway Catenary Systems"],"prefix":"10.3390","volume":"17","author":[{"given":"Peiting","family":"Shan","sequence":"first","affiliation":[{"name":"School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1907-2664","authenticated-orcid":false,"given":"Wei","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Information Mechanics and Sensing Engineering, Xidian University, Xi\u2019an 710071, China"},{"name":"Xi\u2019an Key Laboratory of Advanced Remote Sensing, Xi\u2019an 710071, China"},{"name":"Shaanxi Innovation Center for Multi-Source Fusion Detection and Recognition, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuntian","family":"Lou","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0677-6702","authenticated-orcid":false,"given":"Gabriel","family":"Dauphin","sequence":"additional","affiliation":[{"name":"Laboratory of Information Processing and Transmission, L2TI, Institut Galil\u00e9e, University Paris XIII, Villetaneuse, 93430 Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0267-5824","authenticated-orcid":false,"given":"Wenxing","family":"Bao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, North Minzu University, Yinchuan 750021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Xu, T., Gao, X., Yang, Y., Xu, L., Xu, J., and Wang, Y. 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