{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T23:15:16Z","timestamp":1773270916701,"version":"3.50.1"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2021,2,7]],"date-time":"2021-02-07T00:00:00Z","timestamp":1612656000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,2,7]],"date-time":"2021-02-07T00:00:00Z","timestamp":1612656000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100007128","name":"Natural Science Foundation of Shaanxi Province","doi-asserted-by":"publisher","award":["2015JM6296"],"award-info":[{"award-number":["2015JM6296"]}],"id":[{"id":"10.13039\/501100007128","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1007\/s11042-021-10568-x","type":"journal-article","created":{"date-parts":[[2021,2,9]],"date-time":"2021-02-09T02:50:44Z","timestamp":1612839044000},"page":"15959-15976","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Salient object detection via cross diffusion-based compactness on multiple graphs"],"prefix":"10.1007","volume":"80","author":[{"given":"Fan","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guohua","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,2,7]]},"reference":[{"issue":"11","key":"10568_CR1","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K, Lucchi A, Fua P, S\u00fcsstrunk S (2012) SLIC Superpixels compared to state-ofthe- art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274\u20132282","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"10568_CR2","doi-asserted-by":"publisher","first-page":"2189","DOI":"10.1109\/TPAMI.2012.28","volume":"34","author":"B Alexe","year":"2012","unstructured":"Alexe B, Deselaers T, Ferrari V (2012) Measuring the objectness of image windows. IEEE Trans Pattern Anal Mach Intell 34(11):2189\u20132202","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10568_CR3","unstructured":"Borji A, Cheng M-M, Jiang H, Li J (2014) Salient object detection: a survey. Comput Vis Media (5):117\u2013150"},{"key":"10568_CR4","unstructured":"Cheng MM, Mitra NJ, Huang X, Torr PH, Hu SM (2011) Salient object detection and segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. Citeseer (1):1\u20131"},{"key":"10568_CR5","doi-asserted-by":"crossref","unstructured":"Cheng MM, Warrell J, Lin WY, Zheng S, Vineet V, Crook N (2013) Efficient salient region detection with soft image abstraction. In: 2013 IEEE International Conference on Computer vision (ICCV). IEEE, pp 1529\u20131536","DOI":"10.1109\/ICCV.2013.193"},{"issue":"4","key":"10568_CR6","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1007\/s00530-014-0432-7","volume":"22","author":"ZY Cheng","year":"2016","unstructured":"Cheng ZY, Shen JL, Miao HY (2016) The effects of multiple query evidences on social image retrieval. Multimed Syst 22(4):509\u2013523","journal-title":"Multimed Syst"},{"issue":"4","key":"10568_CR7","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1109\/30.920468","volume":"46","author":"C Christopoulos","year":"2000","unstructured":"Christopoulos C, Skodras A, Ebrahimi T (2000) The jpeg2000 still image coding system: an overview. IEEE Trans Consum Electron 46(4):1103\u20131127","journal-title":"IEEE Trans Consum Electron"},{"issue":"4","key":"10568_CR8","doi-asserted-by":"publisher","first-page":"885","DOI":"10.1109\/TMM.2019.2934833","volume":"22","author":"C Deng","year":"2020","unstructured":"Deng C, Xu Y, Nie F, Tao D (2020) Saliency detection via a multiple self-weighted graph-based manifold ranking. IEEE Trans Multimed 22(4):885\u2013896","journal-title":"IEEE Trans Multimed"},{"key":"10568_CR9","unstructured":"Fan D-P, Cheng M-M, Liu Y, Li T, Borji A (2017) Structure-Measure: A New Way to Evaluate Foreground Maps. Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp 4548\u20134557"},{"key":"10568_CR10","unstructured":"Fan D-P, Gong C, Cao Y, Ren B, Cheng M-M, Borji A (2018) Enhanced-alignment Measure for Binary Foreground Map Evaluation. Proceedings of the 27th International Joint Conference on Artificial Intelligence, pp 698\u2013704"},{"key":"10568_CR11","doi-asserted-by":"crossref","unstructured":"Fan D, Wang W, Cheng M, Shen J (2019) Shifting More Attention to Video Salient Object Detection. 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 8546\u20138556","DOI":"10.1109\/CVPR.2019.00875"},{"issue":"01","key":"10568_CR12","first-page":"3232","volume":"19","author":"V Gopalakrishnan","year":"2011","unstructured":"Gopalakrishnan V, Hu Y, Rajan D (2011) Random walks on graphs for salient object detection in images. IEEE Trans Image Process 19(01):3232\u20133242","journal-title":"IEEE Trans Image Process"},{"key":"10568_CR13","doi-asserted-by":"crossref","unstructured":"Harel J, Koch C, Perona P (2007) Graph-based visual saliency. In: Advances in neural information processing systems, pp 545\u2013552","DOI":"10.7551\/mitpress\/7503.003.0073"},{"key":"10568_CR14","doi-asserted-by":"crossref","unstructured":"Hou X, Zhang L (2007) Saliency detection: A spectral residual approach. In: 2007. CVPR\u201907. IEEE Conference on Computer Vision and Pattern Recognition. IEEE, pp 1\u20138","DOI":"10.1109\/CVPR.2007.383267"},{"issue":"11","key":"10568_CR15","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"1998","unstructured":"Itti L, Koch C, Niebur E (1998) A model of saliency based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254\u20131259","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10568_CR16","doi-asserted-by":"crossref","unstructured":"Jiang B, Zhang L, Lu H, Yang C, Yang MH (2013) Saliency detection via absorbing markov chain. IEEE Int Conf Comput Vis (ICCV):1665\u20131672","DOI":"10.1109\/ICCV.2013.209"},{"key":"10568_CR17","doi-asserted-by":"crossref","unstructured":"Kim J, Han D, Tai Y-W, Kim J (2014) Salient Region Detection via High-Dimensional Color Transform. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 883\u2013890","DOI":"10.1109\/CVPR.2014.118"},{"key":"10568_CR18","unstructured":"Lan R, Zhou Y, Tang Y (2015) Quaternionic weber local descriptor of color images. IEEE Trans Circ Syst Video Technol 27(02):261\u2013274"},{"key":"10568_CR19","doi-asserted-by":"crossref","unstructured":"Li Y, Hou X, Koch C, Rehg JM, Yuille AL (2014) The secrets of salient object segmentation. Georgia Institute of Technology","DOI":"10.1109\/CVPR.2014.43"},{"key":"10568_CR20","doi-asserted-by":"crossref","unstructured":"Li H, Lu H, Lin Z, Shen X, Price B (2015) Inner and inter label propagation: salient object detection in the wild. IEEE Trans Image Process 24(10):3176\u20133186","DOI":"10.1109\/TIP.2015.2440174"},{"key":"10568_CR21","unstructured":"Li G, Yu Y (2015) Visual saliency based on multiscale deep features. IEEE Conf Comput Vis Pattern Recogn (CVPR):5455\u20135463"},{"key":"10568_CR22","unstructured":"Li C, Yuan Y, Cai W, Xia Y, Feng DD (2015) Robust saliency detection via regularized random walks ranking. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 2710\u20132717"},{"issue":"25","key":"10568_CR23","doi-asserted-by":"publisher","first-page":"5012","DOI":"10.1109\/TIP.2016.2602079","volume":"11","author":"G Li","year":"2016","unstructured":"Li G, Yu Y (2016) Visual saliency detection based on multiscale deep CNN features. IEEE Trans Image Process (TIP) 11(25):5012\u20135024","journal-title":"IEEE Trans Image Process (TIP)"},{"key":"10568_CR24","doi-asserted-by":"crossref","unstructured":"Li G, Yu Y (2016) Deep Contrast Learning for Salient Object Detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 478\u2013487","DOI":"10.1109\/CVPR.2016.58"},{"issue":"10","key":"10568_CR25","doi-asserted-by":"publisher","first-page":"12,139","DOI":"10.1007\/s11042-017-4862-z","volume":"77","author":"R Li","year":"2018","unstructured":"Li R, He W, Liu Z, Li Y, Fu Z (2018) Saliency-based adaptive compressive sampling of images using measurement contrast. Multimed Tools Appl 77 (10):12,139\u201312,156","journal-title":"Multimed Tools Appl"},{"key":"10568_CR26","doi-asserted-by":"crossref","unstructured":"Liu T, Sun J, Zheng N-N, Tang X, Shum H-Y (2007) Learning to detect a salient object. Proc IEEE Conf Comput Vis Pattern Recogn (CVPR) (07):1\u20138","DOI":"10.1109\/CVPR.2007.383047"},{"issue":"4","key":"10568_CR27","doi-asserted-by":"publisher","first-page":"1023","DOI":"10.1109\/TCSVT.2018.2823769","volume":"29","author":"Y Liu","year":"2019","unstructured":"Liu Y, Han J, Zhang Q, Wang L (2019) Salient object detection via two-stage graphs. IEEE Trans Circ Syst Video Technol 29(4):1023\u20131037","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"10568_CR28","doi-asserted-by":"crossref","unstructured":"Liu Z, Zhang W, Zhao P (2020) A cross-modal adaptive gated fusion generative adversarial network for RGB-D salient object detection. Neurocomputing 387:210\u2013220","DOI":"10.1016\/j.neucom.2020.01.045"},{"key":"10568_CR29","doi-asserted-by":"crossref","unstructured":"Margolin R, Zelnik-Manor L, Tal A (2014) How to Evaluate Foreground Maps?. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 248\u2013255","DOI":"10.1109\/CVPR.2014.39"},{"key":"10568_CR30","doi-asserted-by":"crossref","unstructured":"Movahedi V, Elder J (2010) Design and perceptual validation of performance measures for salient object segmentation. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition -Workshops, San Francisco, pp 49\u201356","DOI":"10.1109\/CVPRW.2010.5543739"},{"key":"10568_CR31","unstructured":"Na T (2015) Salient object detection via bootstrap learning. IEEE Conf Comput Vis Pattern Recogn (CVPR):1884\u20131892"},{"issue":"4","key":"10568_CR32","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1109\/TPAMI.2016.2562626","volume":"39","author":"H Peng","year":"2017","unstructured":"Peng H, Li B, Ling H, Hu W, Xiong W, Maybank SJ (2017) Salient object detection via structured matrix decomposition. IEEE Trans Pattern Anal Mach Intell 39(4):818\u2013832","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10568_CR33","doi-asserted-by":"crossref","unstructured":"Piao Y, Rong Z, Zhang M, Lu H (2020) Exploit and Replace: An Asymmetrical Two-Stream Architecture for Versatile Light Field Saliency Detection. Proc AAAI Conf Artif Intell 34(07):11865\u201311873","DOI":"10.1609\/aaai.v34i07.6860"},{"key":"10568_CR34","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1016\/j.neucom.2019.08.091","volume":"376","author":"Z Qi","year":"2020","unstructured":"Qi Z, Yu S, You X (2020) Coarse-to-fine salient object detection with low-rank matrix recovery. Neurocomputing 376:232\u2013243","journal-title":"Neurocomputing"},{"key":"10568_CR35","doi-asserted-by":"crossref","unstructured":"Qin Y, Lu H, Xu Y, Wang H (2015) Saliency detection via cellular automata. In: 2015 IEEE Conference on Computer vision and pattern recognition (CVPR). IEEE, pp 110\u2013119","DOI":"10.1109\/CVPR.2015.7298606"},{"key":"10568_CR36","doi-asserted-by":"publisher","first-page":"107266","DOI":"10.1016\/j.patcog.2020.107266","volume":"103","author":"W Qiu","year":"2020","unstructured":"Qiu W, Gao X, Han B (2020) Saliency Detection using a Deep Conditional Random Field Network. Pattern Recogn 103:107266","journal-title":"Pattern Recogn"},{"issue":"5","key":"10568_CR37","doi-asserted-by":"publisher","first-page":"1639","DOI":"10.1109\/TIP.2015.2403241","volume":"24","author":"J Sun","year":"2015","unstructured":"Sun J, Lu H, Liu X (2015) Saliency region detection based on markov absorption probabilities. IEEE Trans Image Process 24(5):1639\u20131649","journal-title":"IEEE Trans Image Process"},{"key":"10568_CR38","unstructured":"Wang J, Jiang H, Yuan Z, Cheng M-M, Hu X, Zheng N (2013) Salient object detection: a discriminative regional feature integration approach. IEEE Conf Comput Vis Pattern Recogn (CVPR):2083\u20132090"},{"key":"10568_CR39","doi-asserted-by":"crossref","unstructured":"Wang L, Lu H, Ruan X, Yang M-H (2015) Deep networks for saliency detection via local estimation and global search. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 3183\u20133192","DOI":"10.1109\/CVPR.2015.7298938"},{"key":"10568_CR40","doi-asserted-by":"crossref","unstructured":"Wang T, Zhang L, Lu H, Sun C, Qi J (2016) Kernelized subspace ranking for saliency detection. Eur Conf Comput Vis:450\u2013466","DOI":"10.1007\/978-3-319-46484-8_27"},{"key":"10568_CR41","doi-asserted-by":"crossref","unstructured":"Wang Q, Zheng W, Piramuthu Grab R (2016) Visual saliency via novel graph model and background priors. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 535\u2013543","DOI":"10.1109\/CVPR.2016.64"},{"key":"10568_CR42","unstructured":"Wang W, Shen J, Shao L (2017) Video Salient Object Detection via Fully Convolutional Networks. IEEE Trans Image Process 1(27):38\u201349"},{"key":"10568_CR43","unstructured":"Wang W, Lai Q, Fu H, Shen J, Ling H (2019) Salient Object Detection in the Deep Learning Era: An In-Depth Survey. CoRR"},{"key":"10568_CR44","doi-asserted-by":"crossref","unstructured":"Wei Y, Wen F, Zhu W, Sun J (2012) Geodesic saliency using background priors. Proc Eur Conf Comput Vis:29\u201342","DOI":"10.1007\/978-3-642-33712-3_3"},{"issue":"28","key":"10568_CR45","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.neucom.2019.09.096","volume":"383","author":"C Xia","year":"2020","unstructured":"Xia C, Zhang H, Gao X, Li K (2020) Exploiting background divergence and foreground compactness for salient object detection. Neurocomputing 383(28):194\u2013211","journal-title":"Neurocomputing"},{"key":"10568_CR46","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1016\/j.neucom.2018.06.072","volume":"315","author":"Y Xiao","year":"2018","unstructured":"Xiao Y, Bo J, Tu Z, Ma J, Tang J (2018) A prior regularized multi-layer graph ranking model for image saliency computation. Neurocomputing 315:234\u2013245","journal-title":"Neurocomputing"},{"issue":"04","key":"10568_CR47","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1016\/j.neucom.2019.03.066","volume":"351","author":"Y Xiao","year":"2019","unstructured":"Xiao Y, Bo J, Zheng A, Zhou A, Hussain A, Tang J (2019) Saliency detection via multi-view graph based saliency optimization. Neurocomputing 351(04):156\u2013166","journal-title":"Neurocomputing"},{"key":"10568_CR48","doi-asserted-by":"crossref","unstructured":"Yan Q, Xu L, Shi J, Jia J (2013) Hierarchical saliency detection. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp 1155\u20131162","DOI":"10.1109\/CVPR.2013.153"},{"issue":"3","key":"10568_CR49","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1109\/TPAMI.2016.2547384","volume":"39","author":"J Yang","year":"2016","unstructured":"Yang J, Yang MH (2016) Top-down visual saliency via joint CRF and dictionary learning. IEEE Trans Pattern Anal Mach Intell 39(3):576\u2013588","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10568_CR50","doi-asserted-by":"crossref","unstructured":"Yang C, Zhang L, Lu H, Ruan X, Yang MH (2013) Saliency detection via graph-based manifold ranking. IEEE Conf Comput Vis Pattern Recogn (CVPR):3166\u20133173","DOI":"10.1109\/CVPR.2013.407"},{"key":"10568_CR51","doi-asserted-by":"crossref","unstructured":"Yu Qiu A, Yun Liu B, Hui Yang B, Jing Xu A (2020) A simple saliency detection approach via automatic top-down feature fusion. Neurocomputing 388:124\u2013134","DOI":"10.1016\/j.neucom.2019.12.123"},{"issue":"29","key":"10568_CR52","first-page":"1","volume":"1","author":"P Yu","year":"2020","unstructured":"Yu P, Yu X, Wu Y, Wu C (2020) FSP: a feedback-based saliency propagation method for saliency detection. J Electronic Imaging 1(29):1\u201318","journal-title":"J Electronic Imaging"},{"key":"10568_CR53","unstructured":"Zhang L, Gu Z, Li H (2014) SDSP: A novel saliency detection method by combining simple priors. IEEE Int Conf Image Process:171\u2013175"},{"issue":"5","key":"10568_CR54","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1109\/TPAMI.2015.2473844","volume":"38","author":"J Zhang","year":"2016","unstructured":"Zhang J, Sclaroff S (2016) Exploiting surroundedness for saliency detection: a boolean map approach. IEEE Trans Pattern Anal Mach Intell 38(5):889\u2013902","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10568_CR55","doi-asserted-by":"crossref","unstructured":"Zhang DW, Han JW, Zhang Y (2017) Supervision by fusion: Towards unsupervised learning of deep salient object detector. IEEE International Conference on Computer Vision (ICCV)","DOI":"10.1109\/ICCV.2017.436"},{"issue":"2","key":"10568_CR56","doi-asserted-by":"publisher","first-page":"987","DOI":"10.1109\/TIP.2017.2766787","volume":"27","author":"L Zhang","year":"2018","unstructured":"Zhang L, Ai J, Jiang B, Lu H, Li X (2018) Saliency detection via absorbing markov chain with learnt transition probability. IEEE Trans Image Process 27(2):987\u2013998","journal-title":"IEEE Trans Image Process"},{"key":"10568_CR57","doi-asserted-by":"crossref","unstructured":"Zhang J, Liu Y, Zhang S, Poppe R, Wang M (2019) Light Field Saliency Detection with Deep Convolutional Networks. IEEE Trans Image Process 29:4421\u20134434","DOI":"10.1109\/TIP.2020.2970529"},{"key":"10568_CR58","doi-asserted-by":"crossref","unstructured":"Zhang Y, Zhang S, Zhang P, Song H, Zhang X (2020) Local Regression Ranking for Saliency Detection. IEEE Trans Image Process (29):1536\u20131547","DOI":"10.1109\/TIP.2019.2942796"},{"key":"10568_CR59","doi-asserted-by":"crossref","unstructured":"Zhao JX, Cao Y, Fan DP, Cheng MM, Li XY, Zhang L (2019) Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection. 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 3922\u20133931","DOI":"10.1109\/CVPR.2019.00405"},{"issue":"11","key":"10568_CR60","doi-asserted-by":"publisher","first-page":"3308","DOI":"10.1109\/TIP.2015.2438546","volume":"24","author":"L Zhou","year":"2015","unstructured":"Zhou L, Yang Z, Yuan Q, Zhou Z, Hu D (2015) Salient region detection via integrating diffusion-based compactness and local contrast. IEEE Trans Image Process 24(11):3308\u20133320","journal-title":"IEEE Trans Image Process"},{"issue":"12","key":"10568_CR61","doi-asserted-by":"publisher","first-page":"5882","DOI":"10.1109\/TIP.2017.2738839","volume":"26","author":"L Zhou","year":"2017","unstructured":"Zhou L., Yang Z., Zhou Z., Hu D. (2017) Salient region detection using diffusion process on a two-layer sparse graph. IEEE Trans Image Process 26(12):5882\u20135894","journal-title":"IEEE Trans Image Process"},{"key":"10568_CR62","doi-asserted-by":"crossref","unstructured":"Zhu W, Liang S, Wei Y, Sun J (2014) Saliency optimization from robust background detection. Proc IEEE Conf Comput Vis Pattern Recognit:2814\u20132821","DOI":"10.1109\/CVPR.2014.360"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10568-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-021-10568-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10568-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T19:00:42Z","timestamp":1697828442000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-021-10568-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,7]]},"references-count":62,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2021,4]]}},"alternative-id":["10568"],"URL":"https:\/\/doi.org\/10.1007\/s11042-021-10568-x","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,7]]},"assertion":[{"value":"16 June 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 September 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 January 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}