{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T14:19:37Z","timestamp":1783174777754,"version":"3.54.6"},"reference-count":52,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100002766","name":"Beijing University of Posts and Telecommunications","doi-asserted-by":"publisher","award":["510224072"],"award-info":[{"award-number":["510224072"]}],"id":[{"id":"10.13039\/501100002766","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010909","name":"Excellent Young Scientists Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010909","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62406035"],"award-info":[{"award-number":["62406035"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.patcog.2026.114016","type":"journal-article","created":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T15:54:47Z","timestamp":1780329287000},"page":"114016","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["ParsingFormer for pixel-wise hierarchical human representation learning"],"prefix":"10.1016","volume":"180","author":[{"given":"Pu","family":"Cao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhixiang","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyi","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanli","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3857-3982","authenticated-orcid":false,"given":"Lu","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.114016_b1","doi-asserted-by":"crossref","DOI":"10.1007\/s11263-024-02031-9","article-title":"Deep learning technique for human parsing: A survey and outlook","author":"Yang","year":"2024","journal-title":"Int. J. Comput. Vis."},{"issue":"4","key":"10.1016\/j.patcog.2026.114016_b2","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1109\/TPAMI.2018.2820063","article-title":"Look into person: Joint body parsing pose estimation network and a new benchmark","volume":"41","author":"Liang","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.114016_b3","doi-asserted-by":"crossref","first-page":"7128","DOI":"10.1109\/TMM.2022.3217413","article-title":"Quality-aware network for human parsing","volume":"25","author":"Yang","year":"2022","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.patcog.2026.114016_b4","doi-asserted-by":"crossref","unstructured":"K. Gong, X. Liang, Y. Li, Y. Chen, M. Yang, L. Lin, Instance-level human parsing via part grouping network, in: European Conference on Computer Vision, 2018, pp. 770\u2013785.","DOI":"10.1007\/978-3-030-01225-0_47"},{"key":"10.1016\/j.patcog.2026.114016_b5","doi-asserted-by":"crossref","unstructured":"X. Zhang, Y. Chen, B. Zhu, J. Wang, M. Tang, Part-aware context network for human parsing, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 8971\u20138980.","DOI":"10.1109\/CVPR42600.2020.00899"},{"key":"10.1016\/j.patcog.2026.114016_b6","doi-asserted-by":"crossref","unstructured":"R. Ji, D. Du, L. Zhang, L. Wen, Y. Wu, C. Zhao, F. Huang, S. Lyu, Learning semantic neural tree for human parsing, in: European Conference on Computer Vision, 2020, pp. 205\u2013221.","DOI":"10.1007\/978-3-030-58601-0_13"},{"key":"10.1016\/j.patcog.2026.114016_b7","doi-asserted-by":"crossref","unstructured":"T. Ruan, T. Liu, Z. Huang, Y. Wei, S. Wei, Y. Zhao, Devil in the details: Towards accurate single and multiple human parsing, in: Proceedings of the AAAI Conference on Artificial Intelligence, 2019, pp. 4814\u20134821.","DOI":"10.1609\/aaai.v33i01.33014814"},{"issue":"6","key":"10.1016\/j.patcog.2026.114016_b8","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1109\/JAS.2022.105647","article-title":"Part decomposition and refinement network for human parsing","volume":"9","author":"Yang","year":"2022","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"10.1016\/j.patcog.2026.114016_b9","doi-asserted-by":"crossref","unstructured":"W. Wang, H. Zhu, J. Dai, Y. Pang, J. Shen, L. Shao, Hierarchical human parsing with typed part-relation reasoning, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 8929\u20138939.","DOI":"10.1109\/CVPR42600.2020.00895"},{"key":"10.1016\/j.patcog.2026.114016_b10","doi-asserted-by":"crossref","unstructured":"T. Zhou, W. Wang, S. Liu, Y. Yang, L.V. Gool, Differentiable multi-granularity human representation learning for instance-aware human semantic parsing, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 1622\u20131631.","DOI":"10.1109\/CVPR46437.2021.00167"},{"key":"10.1016\/j.patcog.2026.114016_b11","doi-asserted-by":"crossref","unstructured":"F. Xia, P. Wang, X. Chen, A.L. Yuille, Joint multi-person pose estimation and semantic part segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 6769\u20136778.","DOI":"10.1109\/CVPR.2017.644"},{"key":"10.1016\/j.patcog.2026.114016_b12","doi-asserted-by":"crossref","unstructured":"J. Zhao, J. Li, Y. Cheng, T. Sim, S. Yan, J. Feng, Understanding humans in crowded scenes: Deep nested adversarial learning and a new benchmark for multi-human parsing, in: Proceedings of the 26th ACM International Conference on Multimedia, 2018, pp. 792\u2013800.","DOI":"10.1145\/3240508.3240509"},{"key":"10.1016\/j.patcog.2026.114016_b13","doi-asserted-by":"crossref","unstructured":"L. Yang, Q. Song, Z. Wang, M. Hu, C. Liu, X. Xin, W. Jia, S. Xu, Renovating parsing r-cnn for accurate multiple human parsing, in: European Conference on Computer Vision, 2020, pp. 421\u2013437.","DOI":"10.1007\/978-3-030-58610-2_25"},{"key":"10.1016\/j.patcog.2026.114016_b14","article-title":"Cpi-parser: Integrating causal properties into multiple human parsing","author":"Wang","year":"2024","journal-title":"IEEE Trans. Image Process."},{"issue":"6","key":"10.1016\/j.patcog.2026.114016_b15","doi-asserted-by":"crossref","first-page":"1744","DOI":"10.1109\/TNNLS.2018.2873722","article-title":"Attention inspiring receptive-fields network for learning invariant representations","volume":"30","author":"Yang","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.patcog.2026.114016_b16","doi-asserted-by":"crossref","unstructured":"K. Liu, O. Choi, J. Wang, W. Hwang, Cdgnet: Class distribution guided network for human parsing, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 4473\u20134482.","DOI":"10.1109\/CVPR52688.2022.00443"},{"key":"10.1016\/j.patcog.2026.114016_b17","doi-asserted-by":"crossref","unstructured":"D. Zeng, Y. Huang, Q. Bao, J. Zhang, C. Su, W. Liu, Neural architecture search for joint human parsing and pose estimation, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 11385\u201311394.","DOI":"10.1109\/ICCV48922.2021.01119"},{"key":"10.1016\/j.patcog.2026.114016_b18","doi-asserted-by":"crossref","unstructured":"W. Wang, Z. Zhang, S. Qi, J. Shen, Y. Pang, L. Shao, Learning compositional neural information fusion for human parsing, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2019, pp. 5703\u20135713.","DOI":"10.1109\/ICCV.2019.00580"},{"key":"10.1016\/j.patcog.2026.114016_b19","doi-asserted-by":"crossref","unstructured":"L. Yang, Q. Song, Z. Wang, M. Jiang, Parsing r-cnn for instance-level human analysis, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 364\u2013373.","DOI":"10.1109\/CVPR.2019.00045"},{"key":"10.1016\/j.patcog.2026.114016_b20","doi-asserted-by":"crossref","unstructured":"J. Hong, H. Yang, Y.J. Kim, H. Kim, S. Kim, E. Shim, K. Lee, D2FP: Learning Implicit Prior for Human Parsing, in: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, WACV, 2025, pp. 9096\u20139106.","DOI":"10.1109\/WACV61041.2025.00883"},{"key":"10.1016\/j.patcog.2026.114016_b21","series-title":"SCHNet: SAM marries CLIP for human parsing","author":"Liu","year":"2025"},{"key":"10.1016\/j.patcog.2026.114016_b22","doi-asserted-by":"crossref","DOI":"10.1109\/TIP.2024.3456004","article-title":"Uniparser: Multi-human parsing with unified correlation representation learning","author":"Chu","year":"2024","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.patcog.2026.114016_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111736","article-title":"Quality transformer for human parsing","volume":"169","author":"Guo","year":"2026","journal-title":"Pattern Recognit."},{"issue":"110879","key":"10.1016\/j.patcog.2026.114016_b24","article-title":"Fcgnet: Foreground and class guided network for human parsing","volume":"157","author":"Jang","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114016_b25","unstructured":"J. Wehrmann, R. Cerri, R. Barros, Hierarchical multi-label classification networks, in: International Conference on Machine Learning, 2018, pp. 5075\u20135084."},{"key":"10.1016\/j.patcog.2026.114016_b26","series-title":"Advances in Neural Information Processing Systems","article-title":"Label embedding trees for large multi-class tasks","author":"Bengio","year":"2010"},{"key":"10.1016\/j.patcog.2026.114016_b27","doi-asserted-by":"crossref","unstructured":"X. Liang, C. Xu, X. Shen, J. Yang, S. Liu, J. Tang, L. Lin, S. Yan, Human parsing with contextualized convolutional neural network, in: Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 1386\u20131394.","DOI":"10.1109\/ICCV.2015.163"},{"key":"10.1016\/j.patcog.2026.114016_b28","doi-asserted-by":"crossref","unstructured":"N. Carion, F. Massa, G. Synnaeve, N. Usunier, A. Kirillov, S. Zagoruyko, End-to-end object detection with transformers, in: European Conference on Computer Vision, 2020, pp. 213\u2013229.","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"10.1016\/j.patcog.2026.114016_b29","doi-asserted-by":"crossref","unstructured":"B. Cheng, I. Misra, A.G. Schwing, A. Kirillov, R. Girdhar, Masked-attention mask transformer for universal image segmentation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 1290\u20131299.","DOI":"10.1109\/CVPR52688.2022.00135"},{"key":"10.1016\/j.patcog.2026.114016_b30","doi-asserted-by":"crossref","unstructured":"F. Milletari, N. Navab, S.-A. Ahmadi, V-net: Fully convolutional neural networks for volumetric medical image segmentation, in: International Conference on 3D Vision, 2016, pp. 565\u2013571.","DOI":"10.1109\/3DV.2016.79"},{"key":"10.1016\/j.patcog.2026.114016_b31","doi-asserted-by":"crossref","unstructured":"M. Berman, A.R. Triki, M.B. Blaschko, The lovasz-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 4413\u20134421.","DOI":"10.1109\/CVPR.2018.00464"},{"key":"10.1016\/j.patcog.2026.114016_b32","doi-asserted-by":"crossref","unstructured":"K. He, X. Zhang, S. Ren, J. Sun, Deep residual learning for image recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"10.1016\/j.patcog.2026.114016_b33","unstructured":"A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, J. Uszkoreit, N. Houlsby, An image is worth 16x16 words: Transformers for image recognition at scale, in: International Conference on Learning Representations, 2020."},{"issue":"31","key":"10.1016\/j.patcog.2026.114016_b34","article-title":"Dinov2: Learning robust visual features without supervision","volume":"1","author":"Oquab","year":"2024","journal-title":"Trans. Mach. Learn. Res. J."},{"key":"10.1016\/j.patcog.2026.114016_b35","series-title":"Towards efficient visual adaption via structural re-parameterization","author":"Luo","year":"2023"},{"issue":"10","key":"10.1016\/j.patcog.2026.114016_b36","doi-asserted-by":"crossref","first-page":"3349","DOI":"10.1109\/TPAMI.2020.2983686","article-title":"Deep high-resolution representation learning for visual recognition","volume":"43","author":"Wang","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"10.1016\/j.patcog.2026.114016_b37","doi-asserted-by":"crossref","first-page":"3260","DOI":"10.1109\/TPAMI.2020.3048039","article-title":"Self-correction for human parsing","volume":"44","author":"Li","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.114016_b38","doi-asserted-by":"crossref","unstructured":"Y. Yuan, X. Chen, J. Wang, Object-contextual representations for semantic segmentation, in: European Conference on Computer Vision, 2020, pp. 173\u2013190.","DOI":"10.1007\/978-3-030-58539-6_11"},{"key":"10.1016\/j.patcog.2026.114016_b39","doi-asserted-by":"crossref","unstructured":"Z. Jin, B. Liu, Q. Chu, N. Yu, Isnet: Integrate image-level and semantic-level context for semantic segmentation, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 7189\u20137198.","DOI":"10.1109\/ICCV48922.2021.00710"},{"key":"10.1016\/j.patcog.2026.114016_b40","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108593","article-title":"Multilabel learning based adaptive graph convolutional network for human parsing","author":"Hao","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114016_b41","doi-asserted-by":"crossref","first-page":"2601","DOI":"10.1109\/TMM.2022.3148595","article-title":"Human parsing with part-aware relation modeling","volume":"25","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.patcog.2026.114016_b42","article-title":"From simple to complex scenes: Learning robust feature representations for accurate human parsing","author":"Liu","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"8","key":"10.1016\/j.patcog.2026.114016_b43","doi-asserted-by":"crossref","first-page":"2185","DOI":"10.1007\/s11263-019-01181-5","article-title":"Fine-grained multi-human parsing","volume":"128","author":"Zhao","year":"2020","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.patcog.2026.114016_b44","doi-asserted-by":"crossref","first-page":"5599","DOI":"10.1109\/TIP.2022.3192989","article-title":"Aiparsing: Anchor-free instance-level human parsing","volume":"31","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.patcog.2026.114016_b45","series-title":"Repparser: End-to-end multiple human parsing with representative parts","author":"Chen","year":"2022"},{"key":"10.1016\/j.patcog.2026.114016_b46","doi-asserted-by":"crossref","unstructured":"J. Chu, L. Jin, J. Xing, J. Zhao, Single-stage multi-human parsing via point sets and center-based offsets, in: Proceedings of the 31th ACM International Conference on Multimedia, 2023, pp. 1863\u20131873.","DOI":"10.1145\/3581783.3611993"},{"key":"10.1016\/j.patcog.2026.114016_b47","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.1109\/TMM.2023.3281070","article-title":"Resparser: Fully convolutional multiple human parsing with representative sets","volume":"26","author":"Dai","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.patcog.2026.114016_b48","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1109\/TMM.2023.3260631","article-title":"End-to-end instance-level human parsing by segmenting persons","volume":"26","author":"Li","year":"2023","journal-title":"IEEE Trans. Multimed."},{"issue":"8","key":"10.1016\/j.patcog.2026.114016_b49","doi-asserted-by":"crossref","first-page":"9520","DOI":"10.1109\/TPAMI.2023.3243223","article-title":"Contextual instance decoupling for instance-level human analysis","volume":"45","author":"Wang","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.114016_b50","doi-asserted-by":"crossref","unstructured":"S. Tang, C. Chen, Q. Xie, M. Chen, Y. Wang, Y. Ci, L. Bai, F. Zhu, H. Yang, L. Yi, R. Zhao, W. Ouyang, Humanbench: Towards general human-centric perception with projector assisted pretraining, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 21970\u201321982.","DOI":"10.1109\/CVPR52729.2023.02104"},{"key":"10.1016\/j.patcog.2026.114016_b51","doi-asserted-by":"crossref","unstructured":"Y. Ci, Y. Wang, M. Chen, S. Tang, L. Bai, F. Zhu, R. Zhao, F. Yu, D. Qi, W. Ouyang, Unihcp: A unified model for human-centric perceptions, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 17840\u201317852.","DOI":"10.1109\/CVPR52729.2023.01711"},{"key":"10.1016\/j.patcog.2026.114016_b52","doi-asserted-by":"crossref","first-page":"5672","DOI":"10.1109\/TPAMI.2025.3552604","article-title":"Hulk: A universal knowledge translator for human-centric tasks","volume":"47","author":"Wang","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326009817?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326009817?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T13:52:49Z","timestamp":1783173169000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326009817"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":52,"alternative-id":["S0031320326009817"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114016","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"ParsingFormer for pixel-wise hierarchical human representation learning","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114016","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114016"}}