{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T01:41:37Z","timestamp":1773193297324,"version":"3.50.1"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T00:00:00Z","timestamp":1726790400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T00:00:00Z","timestamp":1726790400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1007\/s00530-024-01475-w","type":"journal-article","created":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T13:01:47Z","timestamp":1726837307000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["FRBNet: feature-iterative reinforcement and boundary-directed network for camouflaged object detection"],"prefix":"10.1007","volume":"30","author":[{"given":"Yitong","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jindong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiming","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyi","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenyue","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,20]]},"reference":[{"issue":"3","key":"1475_CR1","doi-asserted-by":"publisher","first-page":"2426","DOI":"10.1109\/TIV.2022.3216102","volume":"8","author":"Y Ma","year":"2022","unstructured":"Ma, Y., Zhang, J., Qin, G., Jin, J., Zhang, K., Pan, D., Chen, M.: 3D multi-object tracking based on dual-tracker and DS evidence theory. IEEE Trans. Intell. Veh. 8(3), 2426\u20132436 (2022)","journal-title":"IEEE Trans. Intell. Veh."},{"key":"1475_CR2","first-page":"1","volume":"83","author":"Y Liu","year":"2023","unstructured":"Liu, Y., Shen, X., Lyu, Y., Wang, X.: MCA-Net: multi-cascade attention network for polyp segmentation. Multimedia Tools Appl 83, 1\u201318 (2023)","journal-title":"Multimedia Tools Appl"},{"issue":"8","key":"1475_CR3","doi-asserted-by":"publisher","first-page":"2626","DOI":"10.1109\/TMI.2020.2996645","volume":"39","author":"D-P Fan","year":"2020","unstructured":"Fan, D.-P., Zhou, T., Ji, G.-P., Zhou, Y., Chen, G., Fu, H., Shen, J., Shao, L.: Inf-Net: automatic COVID-19 lung infection segmentation from CT images. IEEE Trans. Med. Imaging 39(8), 2626\u20132637 (2020)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"1475_CR4","unstructured":"Pedersen, M., Bruslund\u00a0Haurum, J., Gade, R., Moeslund, T.B.: Detection of marine animals in a new underwater dataset with varying visibility. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 18\u201326 (2019)"},{"key":"1475_CR5","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1109\/TMM.2020.3046884","volume":"24","author":"F Ye","year":"2020","unstructured":"Ye, F., Huang, C., Cao, J., Li, M., Zhang, Y., Lu, C.: Attribute restoration framework for anomaly detection. IEEE Trans. Multimedia 24, 116\u2013127 (2020)","journal-title":"IEEE Trans. Multimedia"},{"key":"1475_CR6","doi-asserted-by":"publisher","first-page":"15949","DOI":"10.1109\/TPAMI.2023.3311447","volume":"45","author":"J Gao","year":"2023","unstructured":"Gao, J., Chen, M., Xu, C.: Vectorized evidential learning for weakly-supervised temporal action localization. IEEE Trans. Pattern Anal. Mach. Intell. 45, 15949\u201315963 (2023)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1475_CR7","doi-asserted-by":"crossref","unstructured":"Gao, J., Zhang, T., Xu, C.: I know the relationships: zero-shot action recognition via two-stream graph convolutional networks and knowledge graphs. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 8303\u20138311 (2019)","DOI":"10.1609\/aaai.v33i01.33018303"},{"issue":"3","key":"1475_CR8","doi-asserted-by":"publisher","first-page":"1646","DOI":"10.1109\/TCSVT.2021.3075470","volume":"32","author":"J Gao","year":"2021","unstructured":"Gao, J., Xu, C.: Learning video moment retrieval without a single annotated video. IEEE Trans. Circuits Syst. Video Technol. 32(3), 1646\u20131657 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"10","key":"1475_CR9","doi-asserted-by":"publisher","first-page":"3476","DOI":"10.1109\/TPAMI.2020.2985708","volume":"43","author":"J Gao","year":"2020","unstructured":"Gao, J., Zhang, T., Xu, C.: Learning to model relationships for zero-shot video classification. IEEE Trans. Pattern Anal. Mach. Intell. 43(10), 3476\u20133491 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1475_CR10","doi-asserted-by":"crossref","unstructured":"Fan, D.-P., Ji, G.-P., Sun, G., Cheng, M.-M., Shen, J., Shao, L.: Camouflaged object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2777\u20132787 (2020)","DOI":"10.1109\/CVPR42600.2020.00285"},{"key":"1475_CR11","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.cviu.2019.04.006","volume":"184","author":"T-N Le","year":"2019","unstructured":"Le, T.-N., Nguyen, T.V., Nie, Z., Tran, M.-T., Sugimoto, A.: Anabranch network for camouflaged object segmentation. Comput. Vis. Image Underst. 184, 45\u201356 (2019)","journal-title":"Comput. Vis. Image Underst."},{"key":"1475_CR12","unstructured":"Skurowski, P., Abdulameer, H., B\u0142aszczyk, J., Depta, T., Kornacki, A., Kozie\u0142, P.: Animal camouflage analysis: chameleon database. Unpublished manuscript 2(6), 7 (2018)"},{"key":"1475_CR13","doi-asserted-by":"crossref","unstructured":"Lv, Y., Zhang, J., Dai, Y., Li, A., Liu, B., Barnes, N., Fan, D.-P.: Simultaneously localize, segment and rank the camouflaged objects. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11591\u201311601 (2021)","DOI":"10.1109\/CVPR46437.2021.01142"},{"key":"1475_CR14","doi-asserted-by":"crossref","unstructured":"Mei, H., Ji, G.-P., Wei, Z., Yang, X., Wei, X., Fan, D.-P.: Camouflaged object segmentation with distraction mining. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8772\u20138781 (2021)","DOI":"10.1109\/CVPR46437.2021.00866"},{"key":"1475_CR15","doi-asserted-by":"crossref","unstructured":"Zhu, H., Li, P., Xie, H., Yan, X., Liang, D., Chen, D., Wei, M., Qin, J.: I can find you! boundary-guided separated attention network for camouflaged object detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, pp. 3608\u20133616 (2022)","DOI":"10.1609\/aaai.v36i3.20273"},{"key":"1475_CR16","doi-asserted-by":"crossref","unstructured":"Sun, D., Jiang, S., Qi, L.: Edge-aware mirror network for camouflaged object detection. In: 2023 IEEE International Conference on Multimedia and Expo (ICME), pp. 2465\u20132470. IEEE (2023)","DOI":"10.1109\/ICME55011.2023.00420"},{"issue":"5","key":"1475_CR17","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.1109\/TPAMI.2017.2710183","volume":"40","author":"Y Duan","year":"2018","unstructured":"Duan, Y., Lu, J., Feng, J., Zhou, J.: Context-aware local binary feature learning for face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 40(5), 1139\u20131153 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1475_CR18","doi-asserted-by":"publisher","first-page":"4934","DOI":"10.1109\/TCSVT.2023.3245883","volume":"33","author":"Y Liu","year":"2023","unstructured":"Liu, Y., Li, H., Cheng, J., Chen, X.: MSCAF-Net: a general framework for camouflaged object detection via learning multi-scale context-aware features. IEEE Trans. Circuits Syst. Video Technol. 33, 4934\u20134947 (2023)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"10","key":"1475_CR19","doi-asserted-by":"publisher","first-page":"6981","DOI":"10.1109\/TCSVT.2022.3178173","volume":"32","author":"G Chen","year":"2022","unstructured":"Chen, G., Liu, S., Sun, Y., et al.: Camouflaged object detection via context-aware cross-level fusion. IEEE Trans. Circuits Syst. Video Technol. 32(10), 6981\u20136993 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"1475_CR20","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1109\/TCSVT.2021.3126591","volume":"33","author":"J Ren","year":"2021","unstructured":"Ren, J., Hu, X., Zhu, L., Xu, X., Xu, Y., Wang, W., Deng, Z., Heng, P.-A.: Deep texture-aware features for camouflaged object detection. IEEE Trans. Circuits Syst. Video Technol. 33, 1157\u20131167 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"1475_CR21","doi-asserted-by":"crossref","unstructured":"Pang, Y., Zhao, X., Xiang, T.-Z., Zhang, L., Lu, H.: Zoom in and out: a mixed-scale triplet network for camouflaged object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2160\u20132170 (2022)","DOI":"10.1109\/CVPR52688.2022.00220"},{"key":"1475_CR22","doi-asserted-by":"crossref","unstructured":"Zhai, Q., Li, X., Yang, F., Chen, C., Cheng, H., Fan, D.-P.: Mutual graph learning for camouflaged object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12997\u201313007 (2021)","DOI":"10.1109\/CVPR46437.2021.01280"},{"issue":"10","key":"1475_CR23","doi-asserted-by":"publisher","first-page":"4460","DOI":"10.1109\/TNNLS.2020.3017939","volume":"32","author":"R Hou","year":"2020","unstructured":"Hou, R., Ma, B., Chang, H., Gu, X., Shan, S., Chen, X.: IAUnet: global context-aware feature learning for person reidentification. IEEE Trans. Neural Netw. Learn. Syst. 32(10), 4460\u20134474 (2020)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"2","key":"1475_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3558768","volume":"19","author":"J Lin","year":"2023","unstructured":"Lin, J., Tan, X., Xu, K., Ma, L., Lau, R.W.: Frequency-aware camouflaged object detection. ACM Trans. Multimedia Comput. Commun. Appl. 19(2), 1\u201316 (2023)","journal-title":"ACM Trans. Multimedia Comput. Commun. Appl."},{"key":"1475_CR25","doi-asserted-by":"crossref","unstructured":"He, R., Dong, Q., Lin, J., Lau, R.W.: Weakly-supervised camouflaged object detection with scribble annotations. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 781\u2013789 (2023)","DOI":"10.1609\/aaai.v37i1.25156"},{"key":"1475_CR26","doi-asserted-by":"crossref","unstructured":"Wang, W., Xie, E., Li, X., Fan, D.-P., Song, K., Liang, D., Lu, T., Luo, P., Shao, L.: Pyramid vision transformer: A versatile backbone for dense prediction without convolutions. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 568\u2013578 (2021)","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"1475_CR27","first-page":"1","volume":"60","author":"A Li","year":"2021","unstructured":"Li, A., Jiao, L., Zhu, H., Li, L., Liu, F.: Multitask semantic boundary awareness network for remote sensing image segmentation. IEEE Trans. Geosci. Remote Sens. 60, 1\u201314 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1475_CR28","doi-asserted-by":"crossref","unstructured":"Huang, Z., Dai, H., Xiang, T.-Z., Wang, S., Chen, H.-X., Qin, J., Xiong, H.: Feature shrinkage pyramid for camouflaged object detection with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5557\u20135566 (2023)","DOI":"10.1109\/CVPR52729.2023.00538"},{"issue":"7","key":"1475_CR29","doi-asserted-by":"publisher","first-page":"4828","DOI":"10.1109\/TCSVT.2021.3123829","volume":"32","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Zhu, G., Wu, L., Kwong, S., Zhang, H., Zhou, Y.: Multi-task se-network for image splicing localization. IEEE Trans. Circuits Syst. Video Technol. 32(7), 4828\u20134840 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"1475_CR30","doi-asserted-by":"crossref","unstructured":"Wei, J., Wang, S., Huang, Q.: $$\\text{F}^3$$net: fusion, feedback and focus for salient object detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 12321\u201312328 (2020)","DOI":"10.1609\/aaai.v34i07.6916"},{"key":"1475_CR31","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"1475_CR32","doi-asserted-by":"publisher","unstructured":"Fan, D.-P., Cheng, M.-M., Liu, Y., Li, T., Borji, A.: Structure-measure: a new way to evaluate foreground maps. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4548\u20134557 (2017). https:\/\/doi.org\/10.1109\/iccv.2017.487","DOI":"10.1109\/iccv.2017.487"},{"key":"1475_CR33","doi-asserted-by":"crossref","unstructured":"Margolin, R., Zelnik-Manor, L., Tal, A.: How to evaluate foreground maps? In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255 (2014)","DOI":"10.1109\/CVPR.2014.39"},{"key":"1475_CR34","doi-asserted-by":"crossref","unstructured":"Fan, D.-P., Ji, G.-P., Qin, X., Cheng, M.-M.: Cognitive vision inspired object segmentation metric and loss function. Scientia Sin. Inf. 6(6) (2021)","DOI":"10.1360\/SSI-2020-0370"},{"key":"1475_CR35","doi-asserted-by":"crossref","unstructured":"Perazzi, F., Kr\u00e4henb\u00fchl, P., Pritch, Y., Hornung, A.: Saliency filters: contrast based filtering for salient region detection. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 733\u2013740 (2012). IEEE","DOI":"10.1109\/CVPR.2012.6247743"},{"issue":"5","key":"1475_CR36","doi-asserted-by":"publisher","first-page":"5364","DOI":"10.1109\/TIE.2021.3078379","volume":"69","author":"K Wang","year":"2021","unstructured":"Wang, K., Bi, H., Zhang, Y., Zhang, C., Liu, Z., Zheng, S.: $$d^{2}$$c-net: a dual-branch, dual-guidance and cross-refine network for camouflaged object detection. IEEE Trans. Ind. Electron. 69(5), 5364\u20135374 (2021)","journal-title":"IEEE Trans. Ind. Electron."},{"issue":"10","key":"1475_CR37","doi-asserted-by":"publisher","first-page":"6024","DOI":"10.1109\/TPAMI.2021.3085766","volume":"44","author":"D-P Fan","year":"2022","unstructured":"Fan, D.-P., Ji, G.-P., Cheng, M.-M., Shao, L.: Concealed object detection. IEEE Trans. Pattern Anal. Mach. Intell. 44(10), 6024\u20136042 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1475_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108644","volume":"127","author":"M Zhuge","year":"2022","unstructured":"Zhuge, M., Lu, X., Guo, Y., Cai, Z., Chen, S.: CubeNet: X-shape connection for camouflaged object detection. Pattern Recognit. 127, 108644 (2022)","journal-title":"Pattern Recognit."},{"key":"1475_CR39","doi-asserted-by":"crossref","unstructured":"Gao, S.-H., Tan, Y.-Q., Cheng, M.-M., Lu, C., Chen, Y., Yan, S.: Highly efficient salient object detection with 100k parameters. In: European Conference on Computer Vision, pp. 702\u2013721. Springer (2020)","DOI":"10.1007\/978-3-030-58539-6_42"},{"key":"1475_CR40","doi-asserted-by":"crossref","unstructured":"Zhang, J., Yu, X., Li, A., Song, P., Liu, B., Dai, Y.: Weakly-supervised salient object detection via scribble annotations. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12546\u201312555 (2020)","DOI":"10.1109\/CVPR42600.2020.01256"},{"key":"1475_CR41","doi-asserted-by":"crossref","unstructured":"Zhang, J., Fan, D.-P., Dai, Y., Anwar, S., Saleh, F.S., Zhang, T., Barnes, N.: UC-Net: uncertainty inspired RGB-D saliency detection via conditional variational autoencoders. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8582\u20138591 (2020)","DOI":"10.1109\/CVPR42600.2020.00861"},{"key":"1475_CR42","doi-asserted-by":"crossref","unstructured":"Pang, Y., Zhao, X., Zhang, L., Lu, H.: Multi-scale interactive network for salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9413\u20139422 (2020)","DOI":"10.1109\/CVPR42600.2020.00943"},{"key":"1475_CR43","doi-asserted-by":"crossref","unstructured":"Zhou, H., Xie, X., Lai, J.-H., Chen, Z., Yang, L.: Interactive two-stream decoder for accurate and fast saliency detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9141\u20139150 (2020)","DOI":"10.1109\/CVPR42600.2020.00916"},{"key":"1475_CR44","doi-asserted-by":"crossref","unstructured":"Fan, D.-P., Ji, G.-P., Zhou, T., Chen, G., Fu, H., Shen, J., Shao, L.: PraNet: parallel reverse attention network for polyp segmentation. In: International Conference on Medical Image Computing and Computer-assisted Intervention, pp. 263\u2013273. Springer (2020)","DOI":"10.1007\/978-3-030-59725-2_26"},{"key":"1475_CR45","doi-asserted-by":"crossref","unstructured":"Liu, N., Zhang, N., Wan, K., Shao, L., Han, J.: Visual saliency transformer. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4722\u20134732 (2021)","DOI":"10.1109\/ICCV48922.2021.00468"},{"key":"1475_CR46","doi-asserted-by":"crossref","unstructured":"Ke, Y.Y., Tsubono, T.: Recursive contour-saliency blending network for accurate salient object detection. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 2940\u20132950 (2022)","DOI":"10.1109\/WACV51458.2022.00143"},{"key":"1475_CR47","doi-asserted-by":"crossref","unstructured":"Yang, F., Zhai, Q., Li, X., Huang, R., Luo, A., Cheng, H., Fan, D.-P.: Uncertainty-guided transformer reasoning for camouflaged object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4146\u20134155 (2021)","DOI":"10.1109\/ICCV48922.2021.00411"},{"key":"1475_CR48","doi-asserted-by":"crossref","unstructured":"Li, A., Zhang, J., Lv, Y., Liu, B., Zhang, T., Dai, Y.: Uncertainty-aware joint salient object and camouflaged object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10071\u201310081 (2021)","DOI":"10.1109\/CVPR46437.2021.00994"},{"key":"1475_CR49","doi-asserted-by":"crossref","unstructured":"Sun, Y., Chen, G., Zhou, T., Zhang, Y., Liu, N.: Context-aware cross-level fusion network for camouflaged object detection. arXiv preprint arXiv:2105.12555 (2021)","DOI":"10.24963\/ijcai.2021\/142"},{"key":"1475_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108901","volume":"248","author":"T Chen","year":"2022","unstructured":"Chen, T., Xiao, J., Hu, X., Zhang, G., Wang, S.: Boundary-guided network for camouflaged object detection. Knowl. Based Syst. 248, 108901 (2022)","journal-title":"Knowl. Based Syst."},{"key":"1475_CR51","doi-asserted-by":"crossref","unstructured":"Jia, Q., Yao, S., Liu, Y., Fan, X., Liu, R., Luo, Z.: Segment, magnify and reiterate: detecting camouflaged objects the hard way. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4713\u20134722 (2022)","DOI":"10.1109\/CVPR52688.2022.00467"},{"key":"1475_CR52","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108414","volume":"123","author":"G-P Ji","year":"2022","unstructured":"Ji, G.-P., Zhu, L., Zhuge, M., Fu, K.: Fast camouflaged object detection via edge-based reversible re-calibration network. Pattern Recognit. 123, 108414 (2022)","journal-title":"Pattern Recognit."},{"key":"1475_CR53","doi-asserted-by":"crossref","unstructured":"Song, Y., Li, X., Qi, L.: Camouflaged object detection with feature grafting and distractor aware. In: 2023 IEEE International Conference on Multimedia and Expo (ICME), pp. 2459\u20132464. IEEE (2023)","DOI":"10.1109\/ICME55011.2023.00419"}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-024-01475-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-024-01475-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-024-01475-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T18:15:00Z","timestamp":1730139300000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-024-01475-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,20]]},"references-count":53,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,10]]}},"alternative-id":["1475"],"URL":"https:\/\/doi.org\/10.1007\/s00530-024-01475-w","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"value":"0942-4962","type":"print"},{"value":"1432-1882","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,20]]},"assertion":[{"value":"13 April 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 August 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 September 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"279"}}