{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T21:07:45Z","timestamp":1781212065116,"version":"3.54.1"},"reference-count":96,"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\/501100004184","name":"Northeastern University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004184","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.eswa.2026.133133","type":"journal-article","created":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T00:01:48Z","timestamp":1780531308000},"page":"133133","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["BASE: A boundary-aware adaptive semantic evidential framework for open-set skeleton-based action recognition"],"prefix":"10.1016","volume":"331","author":[{"given":"Chao","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3368-6991","authenticated-orcid":false,"given":"Dongyue","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dingyu","family":"Xue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6863-8516","authenticated-orcid":false,"given":"Shizhuo","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1424-798X","authenticated-orcid":false,"given":"Tong","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.133133_bib0001","doi-asserted-by":"crossref","unstructured":"Balasubramanian, L., Kruber, F., Botsch, M., & Deng, K. (2021). Open-set recognition based on the combination of deep learning and ensemble method for detecting unknown traffic scenarios. arXiv preprint arXiv:2105.07635.","DOI":"10.1109\/IV48863.2021.9575433"},{"key":"10.1016\/j.eswa.2026.133133_bib0002","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"13349","article-title":"Evidential deep learning for open set action recognition","author":"Bao","year":"2021"},{"key":"10.1016\/j.eswa.2026.133133_bib0003","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"1563","article-title":"Towards open set deep networks","author":"Bendale","year":"2016"},{"key":"10.1016\/j.eswa.2026.133133_bib0004","unstructured":"Boeken, P., Forr\u00e9, P., & Mooij, J. M. (2024). Are Bayesian networks typically faithful?arXiv preprint arXiv:2410.16004."},{"issue":"1","key":"10.1016\/j.eswa.2026.133133_bib0005","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1186\/s13102-025-01260-w","article-title":"Svm action recognition model based on skeletal key point analysis with posture sensors to help sports training","volume":"17","author":"Cao","year":"2025","journal-title":"BMC Sports Science, Medicine and Rehabilitation"},{"issue":"11","key":"10.1016\/j.eswa.2026.133133_bib0006","first-page":"8065","article-title":"Adversarial reciprocal points learning for open set recognition","volume":"44","author":"Chen","year":"2021","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0007","series-title":"European conference on computer vision","first-page":"507","article-title":"Learning open set network with discriminative reciprocal points","author":"Chen","year":"2020"},{"issue":"1","key":"10.1016\/j.eswa.2026.133133_bib0008","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1007\/s00530-025-02078-9","article-title":"Improving skeleton action recognition with channel-temporal attention and multi-stream feature aggregation","volume":"32","author":"Chen","year":"2026","journal-title":"Multimedia Systems"},{"key":"10.1016\/j.eswa.2026.133133_bib0009","doi-asserted-by":"crossref","first-page":"1496","DOI":"10.1109\/TCCN.2025.3613508","article-title":"Class feature space reconstruction for automatic modulation open set recognition","volume":"12","author":"Chen","year":"2025","journal-title":"IEEE Transactions on Cognitive Communications and Networking"},{"key":"10.1016\/j.eswa.2026.133133_bib0010","series-title":"Icassp 2024-2024 ieee international conference on acoustics, speech and signal processing (icassp)","first-page":"6185","article-title":"Improving open-set recognition with bayesian metric learning","author":"Chen","year":"2024"},{"key":"10.1016\/j.eswa.2026.133133_bib0011","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"13359","article-title":"Channel-wise topology refinement graph convolution for skeleton-based action recognition","author":"Chen","year":"2021"},{"key":"10.1016\/j.eswa.2026.133133_bib0012","series-title":"Computer vision\u2013ECCV 2020: 16th european conference, glasgow, UK, august 23\u201328, 2020, proceedings, part XXIV 16","first-page":"536","article-title":"Decoupling gcn with dropgraph module for skeleton-based action recognition","author":"Cheng","year":"2020"},{"key":"10.1016\/j.eswa.2026.133133_bib0013","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"183","article-title":"Skeleton-based action recognition with shift graph convolutional network","author":"Cheng","year":"2020"},{"issue":"2","key":"10.1016\/j.eswa.2026.133133_bib0014","doi-asserted-by":"crossref","first-page":"2533","DOI":"10.1109\/TPAMI.2022.3169976","article-title":"Toyota smarthome untrimmed: Real-world untrimmed videos for activity detection","volume":"45","author":"Dai","year":"2022","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0015","unstructured":"Denipitiyage, D., Karunanayake, N., Seneviratne, S., & Chawla, S. (2025). RankOOD\u2013class ranking-based out-of-distribution detection. arXiv preprint arXiv:2511.19996."},{"key":"10.1016\/j.eswa.2026.133133_bib0016","first-page":"9175","article-title":"Reducing network agnostophobia","volume":"31","author":"Dhamija","year":"2018","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.133133_bib0017","series-title":"2024 International joint conference on neural networks (IJCNN)","first-page":"1","article-title":"Zero-shot out-of-distribution detection with outlier label exposure","author":"Ding","year":"2024"},{"key":"10.1016\/j.eswa.2026.133133_bib0018","series-title":"Proceedings of the 46th international ACM SIGIR conference on research and development in information retrieval","first-page":"2062","article-title":"Hyperformer: Learning expressive sparse feature representations via hypergraph transformer","author":"Ding","year":"2023"},{"key":"10.1016\/j.eswa.2026.133133_bib0019","series-title":"European conference on computer vision","first-page":"401","article-title":"Skateformer: Skeletal-temporal transformer for human action recognition","author":"Do","year":"2024"},{"key":"10.1016\/j.eswa.2026.133133_bib0020","series-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","first-page":"3371","article-title":"Reconstructing humpty dumpty: Multi-feature graph autoencoder for open set action recognition","author":"Du","year":"2023"},{"key":"10.1016\/j.eswa.2026.133133_bib0021","series-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","first-page":"1485","article-title":"Novel ensemble diversification methods for open-set scenarios","author":"Farber","year":"2022"},{"key":"10.1016\/j.eswa.2026.133133_bib0022","unstructured":"Feng, S., Ge, Y., Du, Y., Chen, M., Wang, C., & Feng, L. (2025). Long-tailed out-of-distribution detection with refined separate class learning. arXiv preprint arXiv:2509.17034."},{"key":"10.1016\/j.eswa.2026.133133_bib0023","doi-asserted-by":"crossref","first-page":"2118","DOI":"10.1109\/TPAMI.2025.3625258","article-title":"A comprehensive survey on evidential deep learning and its applications","volume":"48","author":"Gao","year":"2025","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0024","unstructured":"Gao, X., Liu, J., Li, G., Lyu, Y., Gao, J., Yu, W., Xu, N., Wang, L., Shan, C., Liu, Z. et al. (2025b). Good: Training-free guided diffusion sampling for out-of-distribution detection. arXiv preprint arXiv:2510.17131."},{"key":"10.1016\/j.eswa.2026.133133_bib0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2026.115261","article-title":"Mar-gcn: A meta-action refinement graph convolutional network for skeleton-based human action recognition","volume":"336","author":"Guo","year":"2026","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.eswa.2026.133133_bib0026","doi-asserted-by":"crossref","first-page":"2118","DOI":"10.1109\/TCSVT.2024.3491176","article-title":"Enhancing skeleton-based action recognition with language descriptions from pre-trained large multimodal models","volume":"35","author":"He","year":"2024","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.eswa.2026.133133_bib0027","series-title":"Proceedings of the 2025 international conference on multimedia retrieval","first-page":"424","article-title":"Optimal transport-driven federated out-of-distribution detection in heterogeneous data","author":"He","year":"2025"},{"key":"10.1016\/j.eswa.2026.133133_bib0028","series-title":"Icassp 2025-2025 ieee international conference on acoustics, speech and signal processing (icassp)","first-page":"1","article-title":"Gdda: Semantic ood detection on graphs under covariate shift via score-based diffusion models","author":"He","year":"2025"},{"key":"10.1016\/j.eswa.2026.133133_bib0029","unstructured":"Hendrycks, D. (2016). Gaussian error linear units (gelus). arXiv preprint arXiv:1606.08415."},{"key":"10.1016\/j.eswa.2026.133133_bib0030","unstructured":"Hendrycks, D., & Gimpel, K. (2016). A baseline for detecting misclassified and out-of-distribution examples in neural networks. arXiv preprint arXiv:1610.02136."},{"key":"10.1016\/j.eswa.2026.133133_bib0031","doi-asserted-by":"crossref","DOI":"10.1016\/j.phycom.2026.103030","article-title":"Open set recognition for drone based on deep metric learning","volume":"75","author":"Hong","year":"2026","journal-title":"Physical Communication"},{"issue":"4","key":"10.1016\/j.eswa.2026.133133_bib0032","first-page":"4214","article-title":"Class-specific semantic reconstruction for open set recognition","volume":"45","author":"Huang","year":"2022","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0033","series-title":"Ijcai","first-page":"2466","article-title":"Human action recognition using a temporal hierarchy of covariance descriptors on 3d joint locations","volume":"vol. 13","author":"Hussein","year":"2013"},{"key":"10.1016\/j.eswa.2026.133133_bib0034","doi-asserted-by":"crossref","first-page":"4366","DOI":"10.1007\/s11263-025-02384-9","article-title":"Unknown support prototype set for open set recognition","volume":"133","author":"Jiang","year":"2025","journal-title":"International Journal of Computer Vision"},{"key":"10.1016\/j.eswa.2026.133133_bib0035","series-title":"Subjective logic","volume":"vol. 3","author":"J\u00f8sang","year":"2016"},{"key":"10.1016\/j.eswa.2026.133133_bib0036","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"813","article-title":"Opengan: Open-set recognition via open data generation","author":"Kong","year":"2021"},{"key":"10.1016\/j.eswa.2026.133133_bib0037","article-title":"Zero-shot skeleton-based action recognition with dual visual-text alignment","volume":"171","author":"Kuang","year":"2025","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.eswa.2026.133133_bib0038","doi-asserted-by":"crossref","unstructured":"Lang, H., Zheng, Y., Sun, J., Huang, F., Si, L., & Li, Y. (2022). Estimating soft labels for out-of-domain intent detection. arXiv preprint arXiv:2211.05561.","DOI":"10.18653\/v1\/2022.emnlp-main.18"},{"key":"10.1016\/j.eswa.2026.133133_bib0039","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1109\/LSP.2023.3267975","article-title":"Improved shift graph convolutional network for action recognition with skeleton","volume":"30","author":"Li","year":"2023","journal-title":"IEEE Signal Processing Letters"},{"key":"10.1016\/j.eswa.2026.133133_bib0040","doi-asserted-by":"crossref","first-page":"9601","DOI":"10.1109\/TAES.2025.3556812","article-title":"Hrrp open-set recognition via physics-guided pseudo-ood generation and prior decoupling","volume":"61","author":"Li","year":"2025","journal-title":"IEEE Transactions on Aerospace and Electronic Systems"},{"key":"10.1016\/j.eswa.2026.133133_bib0041","doi-asserted-by":"crossref","first-page":"112476","DOI":"10.1109\/ACCESS.2025.3583930","article-title":"Spatial-temporal transformer for optimizing human health through skeleton-based body sports action recognition","volume":"13","author":"Liang","year":"2025","journal-title":"IEEE Access"},{"key":"10.1016\/j.eswa.2026.133133_bib0042","doi-asserted-by":"crossref","unstructured":"Liang, S., Qian, R., Zhuang, Z., & Xie, C. (2024). Modeling body part interactions for skeleton-text contrastive learning in action recognition. Research Square, 10.21203\/rs.3.rs-4929315\/v1.","DOI":"10.21203\/rs.3.rs-4929315\/v1"},{"key":"10.1016\/j.eswa.2026.133133_bib0043","unstructured":"Ling, Z., Zhao, H., Zhang, C., Ao, X., Wang, Z., Zhang, C., Qin, Z., Zhao, X., Chow, K., Wu, Y. et al. (2026). Adaptive dual-weighting framework for federated learning via out-of-distribution detection. arXiv preprint arXiv:2602.01039."},{"issue":"10","key":"10.1016\/j.eswa.2026.133133_bib0044","doi-asserted-by":"crossref","first-page":"2684","DOI":"10.1109\/TPAMI.2019.2916873","article-title":"Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding","volume":"42","author":"Liu","year":"2019","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129820","article-title":"Local and global spatial\u2013temporal transformer for skeleton-based action recognition","volume":"634","author":"Liu","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.133133_bib0046","doi-asserted-by":"crossref","first-page":"2046","DOI":"10.1109\/TNNLS.2025.3632689","article-title":"A systematic review of skeleton-based action recognition: Methods, challenges, and future directions","volume":"37","author":"Liu","year":"2025","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.eswa.2026.133133_bib0047","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"1872","article-title":"Pmal: Open set recognition via robust prototype mining","volume":"vol. 36","author":"Lu","year":"2022"},{"issue":"2","key":"10.1016\/j.eswa.2026.133133_bib0048","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3760390","article-title":"Out-of-distribution detection: A task-oriented survey of recent advances","volume":"58","author":"Lu","year":"2025","journal-title":"ACM Computing Surveys"},{"key":"10.1016\/j.eswa.2026.133133_bib0049","first-page":"7047","article-title":"Predictive uncertainty estimation via prior networks","volume":"31","author":"Malinin","year":"2018","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"4","key":"10.1016\/j.eswa.2026.133133_bib0050","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3770681","article-title":"Hi-OSCAR: Hierarchical open-set classifier for human activity recognition","volume":"9","author":"McCarthy","year":"2025","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"10.1016\/j.eswa.2026.133133_bib0051","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/TMM.2024.3521774","article-title":"Adaptive pitfall: Exploring the effectiveness of adaptation in skeleton-based action recognition","volume":"27","author":"Miao","year":"2024","journal-title":"IEEE Transactions on Multimedia"},{"key":"10.1016\/j.eswa.2026.133133_bib0052","series-title":"European conference on computer vision","first-page":"365","article-title":"Difficulty-aware simulator for open set recognition","author":"Moon","year":"2022"},{"key":"10.1016\/j.eswa.2026.133133_bib0053","series-title":"2025 International conference on advanced technologies for communications (ATC)","first-page":"1","article-title":"A lightweight and online skeleton-based human gesture recognition for human-collaborative robot interaction","author":"Nguyen","year":"2025"},{"key":"10.1016\/j.eswa.2026.133133_bib0054","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"2307","article-title":"C2ae: Class conditioned auto-encoder for open-set recognition","author":"Oza","year":"2019"},{"key":"10.1016\/j.eswa.2026.133133_bib0055","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"4487","article-title":"Navigating open set scenarios for skeleton-based action recognition","volume":"vol. 38","author":"Peng","year":"2024"},{"key":"10.1016\/j.eswa.2026.133133_bib0056","series-title":"Proceedings of the ieee\/cvf conference on computer vision and pattern recognition","first-page":"11544","article-title":"Deep transfer learning for multiple class novelty detection","author":"Perera","year":"2019"},{"key":"10.1016\/j.eswa.2026.133133_bib0057","series-title":"2020\u202fIEEE Intelligent vehicles symposium (IV)","first-page":"1048","article-title":"Open set driver activity recognition","author":"Roitberg","year":"2020"},{"issue":"7","key":"10.1016\/j.eswa.2026.133133_bib0058","doi-asserted-by":"crossref","first-page":"1757","DOI":"10.1109\/TPAMI.2012.256","article-title":"Toward open set recognition","volume":"35","author":"Scheirer","year":"2012","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0059","series-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","first-page":"1956","article-title":"Ood aware supervised contrastive learning","author":"Seifi","year":"2024"},{"key":"10.1016\/j.eswa.2026.133133_bib0060","first-page":"3183","article-title":"Evidential deep learning to quantify classification uncertainty","volume":"31","author":"Sensoy","year":"2018","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"330\u2013331","key":"10.1016\/j.eswa.2026.133133_bib0061","first-page":"3","article-title":"Dempster-shafer theory","volume":"1","author":"Shafer","year":"1992","journal-title":"Encyclopedia of artificial intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0062","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"1010","article-title":"Ntu rgb+ d: A large scale dataset for 3d human activity analysis","author":"Shahroudy","year":"2016"},{"key":"10.1016\/j.eswa.2026.133133_bib0063","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"12026","article-title":"Two-stream adaptive graph convolutional networks for skeleton-based action recognition","author":"Shi","year":"2019"},{"key":"10.1016\/j.eswa.2026.133133_bib0064","doi-asserted-by":"crossref","first-page":"9532","DOI":"10.1109\/TIP.2020.3028207","article-title":"Skeleton-based action recognition with multi-stream adaptive graph convolutional networks","volume":"29","author":"Shi","year":"2020","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.133133_bib0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2026.103278","article-title":"Ednpos: An open-set skeleton-based human action recognition approach for human-robot collaboration enabled by outlier exposure","volume":"101","author":"Song","year":"2026","journal-title":"Robotics and Computer-Integrated Manufacturing"},{"key":"10.1016\/j.eswa.2026.133133_bib0066","first-page":"16857","article-title":"Mpnet: Masked and permuted pre-training for language understanding","volume":"33","author":"Song","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.133133_bib0067","doi-asserted-by":"crossref","first-page":"12388","DOI":"10.1109\/JIOT.2026.3652146","article-title":"Enhancing open set RFF recognition with cGAN: Generating multiple unknown classes","volume":"13","author":"Sun","year":"2026","journal-title":"IEEE Internet of Things Journal"},{"key":"10.1016\/j.eswa.2026.133133_bib0068","unstructured":"Sundararaman, D., Mehta, N., & Carin, L. (2022). Pseudo-OOD training for robust language models. arXiv preprint arXiv:2210.09132."},{"issue":"6","key":"10.1016\/j.eswa.2026.133133_bib0069","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s42979-025-04118-7","article-title":"Advancing violence detection with graph-based skeleton motion analysis","volume":"6","author":"Tran","year":"2025","journal-title":"SN Computer Science"},{"key":"10.1016\/j.eswa.2026.133133_bib0070","series-title":"International conference on intelligent systems and data science","first-page":"86","article-title":"Violence detection using skeleton data with graph convolutional networks","author":"Tran","year":"2024"},{"key":"10.1016\/j.eswa.2026.133133_bib0071","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.111987","article-title":"Skeleton-based multi-person action recognition towards real-world violence detection","volume":"161","author":"Truong","year":"2025","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0072","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"588","article-title":"Human action recognition by representing 3d skeletons as points in a lie group","author":"Vemulapalli","year":"2014"},{"key":"10.1016\/j.eswa.2026.133133_bib0073","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1109\/TCSVT.2025.3597071","article-title":"Out-of-distribution semantic segmentation with disentangled and calibrated representation","volume":"36","author":"Wan","year":"2025","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.eswa.2026.133133_bib0074","unstructured":"Wang, D., Qiu, R., Bai, G., & Huang, Z. (2025a). Gold: Graph out-of-distribution detection via implicit adversarial latent generation. arXiv preprint arXiv:2502.05780."},{"key":"10.1016\/j.eswa.2026.133133_bib0075","article-title":"Synco-OOD: Synthetic-contrastive learning for graph out-of-distribution detection","volume":"667","author":"Wang","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.133133_bib0076","doi-asserted-by":"crossref","unstructured":"Wang, P., He, K., Mou, Y., Song, X., Wu, Y., Wang, J., Xian, Y., Cai, X., & Xu, W. (2023). App: Adaptive prototypical pseudo-labeling for few-shot ood detection. arXiv preprint arXiv:2310.13380.","DOI":"10.18653\/v1\/2023.findings-emnlp.258"},{"key":"10.1016\/j.eswa.2026.133133_bib0077","doi-asserted-by":"crossref","first-page":"6172","DOI":"10.1109\/TPAMI.2025.3550703","article-title":"Backmix: Regularizing open set recognition by removing underlying fore-background priors","volume":"47","author":"Wang","year":"2025","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0078","unstructured":"Wang, Y., Qin, T., Valle, E., & Abrahao, B. (2025d). BootOOD: Self-supervised out-of-distribution detection via synthetic sample exposure under neural collapse. arXiv preprint arXiv:2511.13539."},{"key":"10.1016\/j.eswa.2026.133133_bib0079","series-title":"International conference on artificial intelligence and statistics","first-page":"3376","article-title":"Posterior uncertainty quantification in neural networks using data augmentation","author":"Wu","year":"2024"},{"key":"10.1016\/j.eswa.2026.133133_bib0080","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"10276","article-title":"Generative action description prompts for skeleton-based action recognition","author":"Xiang","year":"2023"},{"key":"10.1016\/j.eswa.2026.133133_bib0081","doi-asserted-by":"crossref","first-page":"17350","DOI":"10.1109\/JSEN.2025.3556580","article-title":"Llms encounter critical elements prompts: Semantically guided partial supervision skeleton-based action recognition","volume":"25","author":"Xin","year":"2025","journal-title":"IEEE Sensors Journal"},{"key":"10.1016\/j.eswa.2026.133133_bib0082","series-title":"Proceedings of the 31st ACM international conference on multimedia","first-page":"2211","article-title":"Skeleton mixformer: Multivariate topology representation for skeleton-based action recognition","author":"Xin","year":"2023"},{"key":"10.1016\/j.eswa.2026.133133_bib0083","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.129158","article-title":"Skeleton-OOD: An end-to-end skeleton-based model for robust out-of-distribution human action detection","volume":"619","author":"Xu","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.133133_bib0084","series-title":"Proceedings of the AAAI conference on artificial intelligence","article-title":"Spatial temporal graph convolutional networks for skeleton-based action recognition","volume":"vol. 32","author":"Yan","year":"2018"},{"key":"10.1016\/j.eswa.2026.133133_bib0085","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"3474","article-title":"Robust classification with convolutional prototype learning","author":"Yang","year":"2018"},{"issue":"5","key":"10.1016\/j.eswa.2026.133133_bib0086","first-page":"2358","article-title":"Convolutional prototype network for open set recognition","volume":"44","author":"Yang","year":"2020","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.133133_bib0087","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"4016","article-title":"Classification-reconstruction learning for open-set recognition","author":"Yoshihashi","year":"2019"},{"issue":"4","key":"10.1016\/j.eswa.2026.133133_bib0088","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s10846-025-02333-1","article-title":"Human-robot interaction with skeleton-based action recognition and motion prediction","volume":"111","author":"Zeng","year":"2025","journal-title":"Journal of Intelligent & Robotic Systems"},{"key":"10.1016\/j.eswa.2026.133133_bib0089","unstructured":"Zhang, H., Cisse, M., Dauphin, Y. N., & Lopez-Paz, D. (2017). Mixup: Beyond empirical risk minimization. arXiv preprint arXiv:1710.09412."},{"key":"10.1016\/j.eswa.2026.133133_bib0090","series-title":"Chinese conference on pattern recognition and computer vision (PRCV)","first-page":"496","article-title":"Enhancing task identification through pseudo-OOD features for class-incremental learning","author":"Zhang","year":"2024"},{"issue":"2","key":"10.1016\/j.eswa.2026.133133_bib0091","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s00530-025-02162-0","article-title":"Second-order hierarchical graph convolution network for skeleton-based action recognition","volume":"32","author":"Zhang","year":"2026","journal-title":"Multimedia Systems"},{"key":"10.1016\/j.eswa.2026.133133_bib0092","doi-asserted-by":"crossref","first-page":"1198","DOI":"10.1109\/TASLP.2020.2983593","article-title":"Out-of-domain detection for natural language understanding in dialog systems","volume":"28","author":"Zheng","year":"2020","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"},{"key":"10.1016\/j.eswa.2026.133133_bib0093","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"4401","article-title":"Learning placeholders for open-set recognition","author":"Zhou","year":"2021"},{"key":"10.1016\/j.eswa.2026.133133_bib0094","doi-asserted-by":"crossref","first-page":"4602","DOI":"10.1109\/TIP.2025.3586487","article-title":"Zero-shot skeleton-based action recognition with prototype-guided feature alignment","volume":"34","author":"Zhou","year":"2025","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.133133_bib0095","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision","first-page":"12648","article-title":"Adaptive hyper-graph convolution network for skeleton-based human action recognition with virtual connections","author":"Zhou","year":"2025"},{"key":"10.1016\/j.eswa.2026.133133_bib0096","first-page":"1","article-title":"DynaPURLS: Dynamic refinement of part-aware representations for skeleton-based zero-shot action recognition","author":"Zhu","year":"2026","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426020439?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426020439?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T20:55:41Z","timestamp":1781211341000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426020439"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":96,"alternative-id":["S0957417426020439"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.133133","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"BASE: A boundary-aware adaptive semantic evidential framework for open-set skeleton-based action recognition","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.133133","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":"133133"}}