{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T22:26:49Z","timestamp":1774045609873,"version":"3.50.1"},"reference-count":47,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005046","name":"Natural Science Foundation of Heilongjiang Province","doi-asserted-by":"publisher","award":["PL2025F017"],"award-info":[{"award-number":["PL2025F017"]}],"id":[{"id":"10.13039\/501100005046","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.asoc.2026.114884","type":"journal-article","created":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T07:50:59Z","timestamp":1771573859000},"page":"114884","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Attentive view fusion and adversarial geometric training for 3D model classification"],"prefix":"10.1016","volume":"193","author":[{"given":"Xueyao","family":"Gao","sequence":"first","affiliation":[]},{"given":"Yali","family":"Shao","sequence":"additional","affiliation":[]},{"given":"Chunxiang","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2688-4955","authenticated-orcid":false,"given":"Yongzeng","family":"Xue","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.asoc.2026.114884_bib0005","doi-asserted-by":"crossref","DOI":"10.1109\/TITS.2025.3571041","article-title":"Hybrid TrafficAI: a generative AI framework for real-time traffic simulation and adaptive behavior modeling","author":"Bilal","year":"2025","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"19","key":"10.1016\/j.asoc.2026.114884_bib0010","doi-asserted-by":"crossref","first-page":"31422","DOI":"10.1109\/JIOT.2024.3418352","article-title":"Online fault diagnosis of industrial robot using IoRT and hybrid deep learning techniques: an experimental approach","volume":"11","author":"Bilal","year":"2024","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.asoc.2026.114884_bib0015","doi-asserted-by":"crossref","DOI":"10.1109\/JIOT.2025.3598320","article-title":"Enhancing healthcare data integrity and access control using blockchain and industry 5.0","author":"Ahmed","year":"2025","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.asoc.2026.114884_bib0020","doi-asserted-by":"crossref","DOI":"10.1109\/TCE.2025.3620226","article-title":"Optimized attention assisted network for forensic-aware malware detection in consumer electronics","author":"Bilal","year":"2025","journal-title":"IEEE Trans. Consum. Electron."},{"key":"10.1016\/j.asoc.2026.114884_bib0025","series-title":"Proceedings of the IEEE International Conference on Computer Vision","first-page":"945","article-title":"Multi-view convolutional neural networks for 3D shape recognition","author":"Su","year":"2015"},{"issue":"7","key":"10.1016\/j.asoc.2026.114884_bib0030","doi-asserted-by":"crossref","first-page":"5589","DOI":"10.1109\/TCSVT.2024.3358850","article-title":"Pedestrian 3D shape understanding for person re-identification via multi-view learning","volume":"34","author":"Yu","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.asoc.2026.114884_bib0035","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"264","article-title":"GVCNN: group-view convolutional neural networks for 3D shape recognition","author":"Feng","year":"2018"},{"key":"10.1016\/j.asoc.2026.114884_bib0040","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"1850","article-title":"View-GCN: view-based graph convolutional network for 3D shape analysis","author":"Wei","year":"2020"},{"issue":"4","key":"10.1016\/j.asoc.2026.114884_bib0045","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1007\/s11760-021-01923-4","article-title":"Center-push loss for joint view-based 3D model classification and retrieval feature learning","volume":"17","author":"Wang","year":"2023","journal-title":"Signal. Image Video Process."},{"key":"10.1016\/j.asoc.2026.114884_bib0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126872","article-title":"3D model classification based on DRSN and multi-view feature fusion","volume":"273","author":"Gao","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.asoc.2026.114884_bib0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2021.108362","article-title":"Supervised multi-view classification via the sparse learning joint the weighted elastic loss","volume":"191","author":"Lin","year":"2022","journal-title":"Signal Process."},{"issue":"4","key":"10.1016\/j.asoc.2026.114884_bib0060","doi-asserted-by":"crossref","first-page":"3201","DOI":"10.1007\/s00521-021-06588-1","article-title":"Multi-view dual attention network for 3D object recognition","volume":"34","author":"Wang","year":"2022","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.asoc.2026.114884_bib0065","doi-asserted-by":"crossref","DOI":"10.3389\/fnbot.2022.1029968","article-title":"Multi-view softpool attention convolutional networks for 3D model classification","volume":"16","author":"Wang","year":"2022","journal-title":"Front. Neurorobot."},{"key":"10.1016\/j.asoc.2026.114884_bib0070","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"5010","article-title":"RotationNet: joint object categorization and pose estimation using multiviews from unsupervised viewpoints","author":"Kanezaki","year":"2018"},{"key":"10.1016\/j.asoc.2026.114884_bib0075","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.asoc.2026.114884_bib0080","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"4700","article-title":"Densely connected convolutional networks","author":"Huang","year":"2017"},{"key":"10.1016\/j.asoc.2026.114884_bib0085","author":"Dosovitskiy"},{"key":"10.1016\/j.asoc.2026.114884_bib0090","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"10012","article-title":"Swin transformer: hierarchical vision transformer using shifted windows","author":"Liu","year":"2021"},{"key":"10.1016\/j.asoc.2026.114884_bib0095","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"652","article-title":"PointNet: deep learning on point sets for 3D classification and segmentation","author":"Qi","year":"2017"},{"key":"10.1016\/j.asoc.2026.114884_bib0100","article-title":"PointNet++: deep hierarchical feature learning on point sets in a metric space","volume":"30","author":"Qi","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"1","key":"10.1016\/j.asoc.2026.114884_bib0105","first-page":"128","article-title":"An end-to-end fine-grained classification network for 3D point clouds","volume":"35","author":"Bai","year":"2023","journal-title":"J. Comput.-Aided Des. Comput. Graph."},{"issue":"4","key":"10.1016\/j.asoc.2026.114884_bib0110","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3306346.3322959","article-title":"MeshCNN: a network with an edge","volume":"38","author":"Hanocka","year":"2019","journal-title":"ACM Trans. Graph."},{"key":"10.1016\/j.asoc.2026.114884_bib0115","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"8279","article-title":"MeshNet: mesh neural network for 3D shape representation","volume":"vol. 33","author":"Feng","year":"2019"},{"issue":"3","key":"10.1016\/j.asoc.2026.114884_bib0120","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3506694","article-title":"Subdivision-based mesh convolution networks","volume":"41","author":"Hu","year":"2022","journal-title":"ACM Trans. Graph."},{"issue":"4","key":"10.1016\/j.asoc.2026.114884_bib0125","first-page":"101","article-title":"Retrieval method of 3D models driven by multi-modal feature fusion and word embedding","volume":"49","author":"Guan","year":"2023","journal-title":"Comput. Eng."},{"key":"10.1016\/j.asoc.2026.114884_bib0130","series-title":"Proceedings of the 26th ACM International Conference on Multimedia","first-page":"1310","article-title":"PVNet: a joint convolutional network of point cloud and multi-view for 3D shape recognition","author":"You","year":"2018"},{"key":"10.1016\/j.asoc.2026.114884_bib0135","doi-asserted-by":"crossref","first-page":"2866","DOI":"10.1109\/TMM.2023.3304896","article-title":"Robust geometry-dependent attack for 3D point clouds","volume":"26","author":"Liu","year":"2023","journal-title":"IEEE Trans. Multimedia"},{"key":"10.1016\/j.asoc.2026.114884_bib0140","series-title":"2019 IEEE International Conference on Image Processing (ICIP)","first-page":"2279","article-title":"Extending adversarial attacks and defenses to deep 3D point cloud classifiers","author":"Liu","year":"2019"},{"key":"10.1016\/j.asoc.2026.114884_bib0145","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6898","article-title":"MeshAdv: adversarial meshes for visual recognition","author":"Xiao","year":"2019"},{"key":"10.1016\/j.asoc.2026.114884_bib0150","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"4119","article-title":"Towards effective adversarial textured 3D meshes on physical face recognition","author":"Yang","year":"2023"},{"key":"10.1016\/j.asoc.2026.114884_bib0155","author":"Goodfellow"},{"key":"10.1016\/j.asoc.2026.114884_bib0160","author":"Madry"},{"key":"10.1016\/j.asoc.2026.114884_bib0165","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (Cvpr)","first-page":"11513","article-title":"Self-robust 3D point recognition via gather-vector guidance","author":"Dong","year":"2020"},{"key":"10.1016\/j.asoc.2026.114884_bib0170","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6186","article-title":"PointGuard: provably robust 3D point cloud classification","author":"Liu","year":"2021"},{"key":"10.1016\/j.asoc.2026.114884_bib0175","series-title":"International Conference on Machine Learning","first-page":"7472","article-title":"Theoretically principled trade-off between robustness and accuracy","author":"Zhang","year":"2019"},{"key":"10.1016\/j.asoc.2026.114884_bib0180","series-title":"Proceedings International Conference on Shape Modeling and Applications","first-page":"154","article-title":"Matching 3D models with shape distributions","author":"Osada","year":"2001"},{"issue":"5","key":"10.1016\/j.asoc.2026.114884_bib0185","doi-asserted-by":"crossref","first-page":"9062","DOI":"10.3934\/mbe.2023398","article-title":"Combine EfficientNet and CNN for 3D model classification","volume":"20","author":"Gao","year":"2023","journal-title":"Math. Biosci. Eng.: MBE"},{"issue":"2","key":"10.1016\/j.asoc.2026.114884_bib0190","doi-asserted-by":"crossref","first-page":"273","DOI":"10.3390\/electronics12020273","article-title":"GN-CNN: a point cloud analysis method for metaverse applications","volume":"12","author":"Sun","year":"2023","journal-title":"Electronics"},{"issue":"2","key":"10.1016\/j.asoc.2026.114884_bib0195","first-page":"303","article-title":"3D model classification and retrieval based on CNN and voting scheme","volume":"31","author":"Bai","year":"2019","journal-title":"J. Comput.-Aided Des. Comput. Graph."},{"issue":"8","key":"10.1016\/j.asoc.2026.114884_bib0200","doi-asserted-by":"crossref","first-page":"3986","DOI":"10.1109\/TIP.2019.2904460","article-title":"3D2SeqViews: aggregating sequential views for 3D global feature learning by CNN with hierarchical attention aggregation","volume":"28","author":"Han","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.asoc.2026.114884_bib0205","author":"Chen"},{"issue":"1","key":"10.1016\/j.asoc.2026.114884_bib0210","doi-asserted-by":"crossref","first-page":"1479","DOI":"10.1007\/s11227-021-03899-x","article-title":"A voxelized point clouds representation for object classification and segmentation on 3D data","volume":"78","author":"Gezawa","year":"2022","journal-title":"J. Supercomput."},{"issue":"2","key":"10.1016\/j.asoc.2026.114884_bib0215","first-page":"322","article-title":"Multimodal 3D model retrieval based on compact center loss","volume":"51","author":"Long","year":"2025","journal-title":"Comput. Eng."},{"key":"10.1016\/j.asoc.2026.114884_bib0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.112298","article-title":"Fuse metaformer with convolutional neural networks for three-dimensional model classification","volume":"161","author":"Gao","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.asoc.2026.114884_bib0225","series-title":"European Conference on Computer Vision","first-page":"628","article-title":"3D-R2N2: a unified approach for single and multi-view 3D object reconstruction","author":"Choy","year":"2016"},{"issue":"1","key":"10.1016\/j.asoc.2026.114884_bib0230","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-07790-0","article-title":"XAI-XGBoost: an innovative explainable intrusion detection approach for securing internet of medical things systems","volume":"15","author":"Hosain","year":"2025","journal-title":"Sci. Rep."},{"issue":"9","key":"10.1016\/j.asoc.2026.114884_bib0235","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.3390\/diagnostics15091059","article-title":"Classification of intraoral photographs with deep learning algorithms trained according to cephalometric measurements","volume":"15","author":"Kartbak","year":"2025","journal-title":"Diagnostics"}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626003327?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626003327?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T20:52:05Z","timestamp":1774039925000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494626003327"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":47,"alternative-id":["S1568494626003327"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2026.114884","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Attentive view fusion and adversarial geometric training for 3D model classification","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2026.114884","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114884"}}