{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:13:15Z","timestamp":1760058795487,"version":"build-2065373602"},"reference-count":18,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T00:00:00Z","timestamp":1745625600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences","award":["CI2023C003YG"],"award-info":[{"award-number":["CI2023C003YG"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In the context of ear-based biometric identity authentication, symmetry between the left and right ears emerges as a pivotal factor, particularly when registration involves one ear and authentication utilizes its contralateral counterpart. The extent to which bilateral ear symmetry supports consistent identity verification warrants significant investigation. This study addresses this challenge by proposing a novel framework, the Symmetry Alignment\u2013Feature Interaction Network, designed to enhance authentication robustness. The proposed network incorporates a Symmetry Alignment Module, leveraging differentiable geometric alignment and a dual-attention mechanism to achieve precise feature correspondence between the left and right ears, thereby mitigating the robustness deficiencies of conventional methods under pose variations. Additionally, a Feature Interaction Network is introduced to amplify nonlinear interdependencies between binaural features, employing a difference\u2013product dual-path architecture to enhance feature discriminability through Dual-Path Feature Interaction and Similarity Fusion. Experimental validation on a dataset from the University of Science and Technology of Beijing demonstrates that the proposed method achieves a similarity detection accuracy of 99.03% (a 9.11% improvement over the baseline ResNet18) and an F1 score of 0.9252 in identity authentication tasks. Ablation experiments further confirm the efficacy of the Symmetry Alignment Module, reducing the false positive rate by 3.05%, in combination with the Feature Interaction Network, shrinking the standard deviation of similarity distributions between the positive and negative samples by 67%. A multi-task loss function, governed by a dynamic weighting mechanism, effectively balances feature learning objectives. This work establishes a new paradigm for the authentication of biometric features with symmetry, integrating symmetry modeling with Dual-Path Feature Interaction and Similarity Fusion to advance the precision of ear authentication.<\/jats:p>","DOI":"10.3390\/sym17050654","type":"journal-article","created":{"date-parts":[[2025,5,2]],"date-time":"2025-05-02T11:35:13Z","timestamp":1746185713000},"page":"654","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Symmetry Alignment\u2013Feature Interaction Network for Human Ear Similarity Detection and Authentication"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-6172-6322","authenticated-orcid":false,"given":"Li","family":"Yuan","sequence":"first","affiliation":[{"name":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China"},{"name":"Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-0899-2974","authenticated-orcid":false,"given":"He-Bin","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China"},{"name":"Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiang-Yun","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China"},{"name":"Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China"},{"name":"Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao-Chai","family":"Gu","sequence":"additional","affiliation":[{"name":"Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ya-Nan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,26]]},"reference":[{"key":"ref_1","unstructured":"Antakis, S. 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