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Inspired by symmetry principles in feature space optimization, the framework integrates (1) a Reverse Attention-based Feature Fusion (RAFF) module aligning cross-domain features using symmetry-guided prototype interactions that enforce bidirectional style-invariant representations and (2) a Self-Correcting Pseudo-Label Loss (SCPL) dynamically adjusting confidence thresholds using entropy symmetry constraints to balance source-target domain knowledge transfer. Experiments demonstrate 92.1% rank-1 accuracy on power industry benchmarks, outperforming DDAG and MTL by 9.5%, with validation confirming robustness in operational deployments. The symmetric design principles significantly enhance model adaptability to inherent symmetry breaking caused by heterogeneous power grid environments.<\/jats:p>","DOI":"10.3390\/sym17050672","type":"journal-article","created":{"date-parts":[[2025,5,2]],"date-time":"2025-05-02T11:35:13Z","timestamp":1746185713000},"page":"672","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Symmetry-Guided Prototype Alignment and Entropy Consistency for Multi-Source Pedestrian ReID in Power Grids: A Domain Adaptation Framework"],"prefix":"10.3390","volume":"17","author":[{"given":"Jia","family":"He","sequence":"first","affiliation":[{"name":"Faculty of Data Science, City University of Macau, Macau 999078, China"},{"name":"School of Applied Science and Civil Engineering, Beijing Institute of Technology, Zhuhai 519087, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1961-3176","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Transportation Engineering, Tongji University, Shanghai 200070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Technology, Beijing Institute of Technology, Zhuhai 519087, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tong","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kejun","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Technology, Beijing Institute of Technology, Zhuhai 519087, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengsheng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Technology, Beijing Institute of Technology, Zhuhai 519087, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xia","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Technology, Beijing Institute of Technology, Zhuhai 519087, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1733","DOI":"10.1007\/s40747-023-01229-7","article-title":"A comprehensive review of pedestrian re-identification based on deep learning","volume":"10","author":"Sun","year":"2024","journal-title":"Complex Intell. 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