{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T12:56:47Z","timestamp":1742389007185,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T00:00:00Z","timestamp":1724716800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T00:00:00Z","timestamp":1724716800000},"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":["Cogn Comput"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s12559-024-10334-9","type":"journal-article","created":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T08:03:11Z","timestamp":1724745791000},"page":"2902-2915","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Image Retrieval Using Multilayer Feature Aggregation Histogram"],"prefix":"10.1007","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8122-1451","authenticated-orcid":false,"given":"Fen","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1558-2694","authenticated-orcid":false,"given":"Guang-Hai","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0078-5675","authenticated-orcid":false,"given":"Xiao-Zhi","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,27]]},"reference":[{"key":"10334_CR1","doi-asserted-by":"publisher","first-page":"107926","DOI":"10.1016\/j.patcog.2021.107926","volume":"116","author":"G-H Liu","year":"2021","unstructured":"Liu G-H, Yang J-Y. Deep-seated features histogram: A novel image retrieval method. Pattern Recogn. 2021;116:107926.","journal-title":"Pattern Recogn"},{"issue":"6","key":"10334_CR2","doi-asserted-by":"publisher","first-page":"7270","DOI":"10.1109\/TPAMI.2022.3218591","volume":"45","author":"W Chen","year":"2023","unstructured":"Chen W, Liu Y, Wang W, Bakker EM, Georgiou T, Fieguth P, et al. Deep learning for instance retrieval: A survey. IEEE Trans Pattern Anal Mach Intell. 2023;45(6):7270\u201392.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"7","key":"10334_CR3","doi-asserted-by":"publisher","first-page":"2380","DOI":"10.1016\/j.patcog.2010.02.012","volume":"43","author":"G-H Liu","year":"2010","unstructured":"Liu G-H, Zhang L, Hou Y-K, Li Z-Y, Yang J-Y. Image retrieval based on multi-texton histogram. Pattern Recogn. 2010;43(7):2380\u20139.","journal-title":"Pattern Recogn"},{"issue":"5802","key":"10334_CR4","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1038\/290091a0","volume":"290","author":"B Julesz","year":"1981","unstructured":"Julesz B. Textons, the elements of texture perception, and their interactions. Nature. 1981;290(5802):91\u20137.","journal-title":"Nature"},{"key":"10334_CR5","unstructured":"Geirhos R, Rubisch P, Michaelis C, Bethge M, Wichmann F, Brendel W.\u00a0ImageNet-trained\u00a0CNNs are biased towards texture, increasing shape bias improves accuracy and robustness. In: Int Conf Learn Rep, New Orleans, LA, USA. 2019. https:\/\/openreview.net\/forum?id=Bygh9j09KX."},{"key":"10334_CR6","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436\u201344.","journal-title":"Nature"},{"key":"10334_CR7","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1113\/jphysiol.1962.sp006837","volume":"160","author":"D Hubel","year":"1962","unstructured":"Hubel D, Wiesel TN. Receptive fields, Binocular interaction and functional architecture in the cat\u2019s visual cortex. J Physiol. 1962;160:106\u201354.","journal-title":"J Physiol"},{"issue":"3","key":"10334_CR8","doi-asserted-by":"publisher","first-page":"538","DOI":"10.1016\/j.neuron.2020.07.037","volume":"108","author":"Y Liu","year":"2020","unstructured":"Liu Y, Li M, Zhang X, Lu Y, Gong H, Yin J, et al. Hierarchical representation for chromatic processing across Macaque V1, V2, and V4. Neuron. 2020;108(3):538-550.e5.","journal-title":"Neuron"},{"key":"10334_CR9","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1038\/s41467-022-35654-y","volume":"14","author":"K Iigaya","year":"2023","unstructured":"Iigaya K, Yi S, Wahle IA, Tanwisuth S, Cross L, O\u2019Doherty J. Neural mechanisms underlying the hierarchical construction of perceived aesthetic value. Nat Commun. 2023;14:127.","journal-title":"Nat Commun"},{"key":"10334_CR10","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1038\/s41586-020-03115-5","volume":"591","author":"A Bongioanni","year":"2021","unstructured":"Bongioanni A, Folloni D, Verhagen L, Sallet J, Klein-Flugge M, Rushworth M. Activation and disruption of a neural mechanism for novel choice in monkeys. Nature. 2021;591:270\u20134.","journal-title":"Nature"},{"key":"10334_CR11","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.jvcir.2015.07.012","volume":"32","author":"A Alzu\u2019bi","year":"2015","unstructured":"Alzu\u2019bi A, Amira A, Ramzan N. Semantic content-based image retrieval: A comprehensive study. J Vis Commun Image Represent. 2015;32:20\u201354.","journal-title":"J Vis Commun Image Represent"},{"issue":"7","key":"10334_CR12","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","volume":"24","author":"T Ojala","year":"2002","unstructured":"Ojala T, Pietikainen M, Maenpaa T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans Pattern Anal Mach Intell. 2002;24(7):971\u201387.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10334_CR13","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe DG. Distinctive image features from scale-invariant key-points. Int J Comput Vis. 2004;60:91\u2013110.","journal-title":"Int J Comput Vis"},{"issue":"3","key":"10334_CR14","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","volume":"110","author":"H Bay","year":"2008","unstructured":"Bay H, Ess A, Tuytelaars T, Gool LV. Speeded-up robust features (SURF). Comput Vis Image Underst. 2008;110(3):346\u201359.","journal-title":"Comput Vis Image Underst"},{"issue":"1","key":"10334_CR15","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/0010-0285(80)90005-5","volume":"12","author":"AM Treisman","year":"1980","unstructured":"Treisman AM, Gelade G. A feature-integration theory of attention. Cogn Psychol. 1980;12(1):97\u2013136.","journal-title":"Cogn Psychol"},{"key":"10334_CR16","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1109\/WIAMIS.2008.24","volume-title":"International Workshop on Image Analysis for\u00a0Multimedia Interactive Service, Klagenfurt, Austria","author":"SA Chatzichristoffs","year":"2008","unstructured":"Chatzichristoffs SA, Boutalis YS.\u00a0FCTH: Fuzzy color and texture histogram - a low level\u00a0feature for accurate image retrieval. In:\u00a0International Workshop on Image Analysis for\u00a0Multimedia Interactive Service, Klagenfurt, Austria. 2008. p. 191\u20136. https:\/\/doi.org\/10.1109\/WIAMIS.2008.24."},{"issue":"1","key":"10334_CR17","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.csi.2010.03.004","volume":"33","author":"XY Wang","year":"2011","unstructured":"Wang XY, Yu YJ, Yang HY. An effective image retrieval scheme using color, texture and shape features. Comput Stand Inter. 2011;33(1):59\u201368.","journal-title":"Comput Stand Inter"},{"key":"10334_CR18","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1016\/j.neucom.2012.08.061","volume":"120","author":"J Yu","year":"2013","unstructured":"Yu J, Qin Z, Wan T, Zhang X. Feature integration analysis of bag-of-features model for image retrieval. Neurocomputing. 2013;120:355\u201364.","journal-title":"Neurocomputing"},{"issue":"12","key":"10334_CR19","doi-asserted-by":"publisher","first-page":"2573","DOI":"10.1109\/TPAMI.2015.2417573","volume":"37","author":"S Zhang","year":"2015","unstructured":"Zhang S, Yang M, Wang X, Lin Y, Tian Q. Semantic-aware co-indexing for image retrieval. IEEE Trans Pattern Anal Mach Intell. 2015;37(12):2573\u201387.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"12","key":"10334_CR20","doi-asserted-by":"publisher","first-page":"5809","DOI":"10.1109\/TIP.2019.2901407","volume":"28","author":"S Kan","year":"2019","unstructured":"Kan S, Cen Y, He Z, Zhang Z, Zhang L, Wang Y. Supervised deep feature embedding with handcrafted feature. IEEE Trans Image Process. 2019;28(12):5809\u201323.","journal-title":"IEEE Trans Image Process"},{"issue":"3","key":"10334_CR21","doi-asserted-by":"publisher","first-page":"1389","DOI":"10.1109\/TNNLS.2020.2984676","volume":"32","author":"S Liu","year":"2021","unstructured":"Liu S, Sun M, Feng L, Qiao H, Chen S, Liu Y. Social neighborhood graph and multigraph fusion ranking for multifeature image retrieval. IEEE Trans Neural Netw Learn Syst. 2021;32(3):1389\u201399.","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"5","key":"10334_CR22","doi-asserted-by":"publisher","first-page":"1154","DOI":"10.1109\/TPAMI.2017.2676779","volume":"40","author":"W Zhou","year":"2018","unstructured":"Zhou W, Li H, Sun J, Tian Q. Collaborative index embedding for image retrieval. IEEE Trans Pattern Anal Mach Intell. 2018;40(5):1154\u201366.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"12","key":"10334_CR23","doi-asserted-by":"publisher","first-page":"7913","DOI":"10.1109\/TNNLS.2021.3084633","volume":"33","author":"P Staszewski","year":"2022","unstructured":"Staszewski P, Jaworski M, Cao J, Rutkowski L. A new approach to descriptors generation for image retrieval by analyzing activations of deep neural network layers. IEEE Trans Neural Netw Learn Syst. 2022;33(12):7913\u201320.","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"11","key":"10334_CR24","doi-asserted-by":"publisher","first-page":"2878","DOI":"10.1109\/TMM.2019.2915036","volume":"21","author":"Z Zhang","year":"2019","unstructured":"Zhang Z, Xie Y, Zhang W, Tian Q. Effective image retrieval via multilinear multi-index fusion. IEEE Trans Multimedia. 2019;21(11):2878\u201390.","journal-title":"IEEE Trans Multimedia"},{"issue":"4","key":"10334_CR25","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TPAMI.2007.70716","volume":"30","author":"A Bosch","year":"2008","unstructured":"Bosch A, Zisserman A, Munoz X. Scene classification using a hybrid generative\/discriminative approach. IEEE Trans Pattern Anal Mach Intell. 2008;30(4):712\u201327.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"10334_CR26","doi-asserted-by":"publisher","first-page":"2133","DOI":"10.1109\/TCSVT.2021.3087823","volume":"32","author":"C Cui","year":"2022","unstructured":"Cui C, Shen Z, Huang J, Chen M, Xu M, Wang M, et al. Adaptive feature aggregation in deep multi-task convolutional neural networks. IEEE Trans Circuits Syst Video Technol. 2022;32(4):2133\u201344.","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"10334_CR27","doi-asserted-by":"publisher","first-page":"1736","DOI":"10.1007\/s12559-023-10143-6","volume":"15","author":"F Lu","year":"2023","unstructured":"Lu F, Liu G-H. Image retrieval using object semantic aggregation histogram. Cogn Comput. 2023;15:1736\u201347. https:\/\/doi.org\/10.1007\/s12559-023-10143-6.","journal-title":"Cogn Comput"},{"key":"10334_CR28","volume-title":"Int Conf Learn Rep, San Diego, CA, USA","author":"K Simonyan","year":"2015","unstructured":"Simonyan K, Zisserman A.\u00a0A. Very deep convolutional networks for large-scale image\u00a0recognition. In: Int Conf Learn Rep, San Diego, CA, USA. 2015. https:\/\/arxiv.org\/abs\/1409.1556."},{"key":"10334_CR29","doi-asserted-by":"publisher","first-page":"770","DOI":"10.1109\/CVPR.2016.90","volume-title":"IEEE IEEE Conf Comput Vis Pattern Recognit, Las Vegas, NV, USA","author":"K He","year":"2016","unstructured":"He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. In: IEEE IEEE Conf Comput Vis Pattern Recognit, Las Vegas, NV, USA. 2016. p. 770\u20138. https:\/\/doi.org\/10.1109\/CVPR.2016.90."},{"key":"10334_CR30","doi-asserted-by":"publisher","first-page":"2261","DOI":"10.1109\/CVPR.2017.243","volume-title":"IEEE Conference on Computer IEEE Conf Comput Vis Pattern Recognit, Honolulu, HI, USA","author":"G Huang","year":"2017","unstructured":"Huang G, Lui Z, Van Der Maaten L, Weinberger KQ.\u00a0Densely connected convolutional\u00a0networks. In: IIEEE Conf Comput Vis Pattern Recognit, Honolulu, HI, USA. 2017. p. 2261\u20139.\u00a0https:\/\/doi.org\/10.1109\/CVPR.2017.243."},{"key":"10334_CR31","doi-asserted-by":"publisher","first-page":"13728","DOI":"10.1109\/CVPR46437.2021.01352","volume-title":"IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR), Nashville, TN, USA","author":"X Ding","year":"2021","unstructured":"Ding X, Zhang X, Ma N, Han J, Ding G, Sun J. RepVGG: Making VGG-style ConvNets great again. In: IEEE\/CVF IEEE Conf Comput Vis Pattern Recognit (CVPR), Nashville, TN, USA. 2021. p. 13728\u201337. https:\/\/doi.org\/10.1109\/CVPR46437.2021.01352."},{"issue":"6","key":"10334_CR32","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1109\/34.862195","volume":"22","author":"SC Zhu","year":"2000","unstructured":"Zhu SC, Liu XW, Wu YN. Exploring texture ensembles by efficient Markov chain Monte Carlo \u2013 toward a \u201ctrichromacy\u201d theory of texture. IEEE Trans Pattern Anal Mach Intell. 2000;22(6):554\u201369.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"10334_CR33","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1109\/TIP.2017.2763829","volume":"27","author":"R Sarkar","year":"2018","unstructured":"Sarkar R, Acton ST. SDL: Saliency-based dictionary learning framework for image similarity. IEEE Trans Image Process. 2018;27(2):749\u201363.","journal-title":"IEEE Trans Image Process"},{"key":"10334_CR34","doi-asserted-by":"publisher","first-page":"103457","DOI":"10.1016\/j.dsp.2022.103457","volume":"123","author":"F Lu","year":"2022","unstructured":"Lu F, Liu G-H. Image retrieval using contrastive weight aggregation histograms. Digit Signal Process. 2022;123:103457.","journal-title":"Digit Signal Process"},{"issue":"01","key":"10334_CR35","doi-asserted-by":"publisher","first-page":"2252003","DOI":"10.1142\/S0218001422520036","volume":"36","author":"B-J Zhang","year":"2022","unstructured":"Zhang B-J, Liu G-H, Hu J-K. Filtering deep convolutional features for image retrieval. Int J Pattern Recognit Artif Intell. 2022;36(01):2252003.","journal-title":"Int J Pattern Recognit Artif Intell"},{"key":"10334_CR36","first-page":"685","volume":"9913","author":"Y Kalantidis","year":"2016","unstructured":"Kalantidis Y, Mellina C, Osindero S. Cross-dimensional weighting for aggregated deep convolutional features. Eur Conf Comput Vis. 2016;9913:685\u2013701.","journal-title":"Eur Conf Comput Vis"},{"key":"10334_CR37","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1016\/j.jvcir.2019.06.006","volume":"62","author":"J Zhu","year":"2019","unstructured":"Zhu J, Wang J, Pang S, Guan W, Li Z, Li Y, et al. Co-weighting semantic convolutional features for object retrieval. J Vis Commun Image Represent. 2019;62:368\u201380.","journal-title":"J Vis Commun Image Represent"},{"issue":"7","key":"10334_CR38","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1109\/TPAMI.2018.2846566","volume":"41","author":"F Radenovi\u0107","year":"2019","unstructured":"Radenovi\u0107 F, Tolias G, Chum O. Fine-tuning CNN image retrieval with no human annotation. IEEE Trans Pattern Anal Mach Intell. 2019;41(7):1655\u201368.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10334_CR39","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.ins.2021.06.002","volume":"577","author":"J Zhou","year":"2021","unstructured":"Zhou J, Gan J, Gao W, Liang A. Image retrieval based on aggregated deep features weighted by regional significance and channel sensitivity. Inf Sci. 2021;577:69\u201380.","journal-title":"Inf Sci"},{"key":"10334_CR40","unstructured":"MathWorks. Singular value decomposition - MATLAB svd. URL: https:\/\/www.mathworks.com\/help\/matlab\/ref\/double.svd.html. Accessed 7 Sept 2023."},{"key":"10334_CR41","doi-asserted-by":"publisher","unstructured":"Philbin J, Chum O, Isard M, Sivic J, Zisserman A. Object retrieval with large vocabularies\u00a0and fast spatial matching. In: IEEE Conf Comput Vis Pattern Recognit, Minneapolis, MN, USA. 2007. p. 1\u20138. https:\/\/doi.org\/10.1109\/CVPR.2007.383172.","DOI":"10.1109\/CVPR.2007.383172"},{"key":"10334_CR42","doi-asserted-by":"publisher","unstructured":"Philbin J, Chum O, Isard M, Sivic J, Zisserman A. Lost in quantization: Improving particular object retrieval in large scale image databases. In: IEEE Conf Comput Vis Pattern Recognit, Anchorage, AK, USA. 2008. p. 1\u20138. https:\/\/doi.org\/10.1109\/CVPR.2008.4587635.","DOI":"10.1109\/CVPR.2008.4587635"},{"key":"10334_CR43","doi-asserted-by":"publisher","unstructured":"Radenovic F, Iscen A, Tolias G, Avrithis Y, Chum O. Revisiting Oxford and Paris: Largescale image retrieval benchmarking. In: IEEE\/CVF Conf Comput Vis Pattern Recognit, Salt Lake City, UT, USA. 2018. p. 5706\u201315. https:\/\/doi.org\/10.1109\/CVPR.2018.00598.","DOI":"10.1109\/CVPR.2018.00598"},{"key":"10334_CR44","doi-asserted-by":"publisher","unstructured":"Jegou H, Douze M, Schmid C. Hamming embedding and weak geometric consistency for large scale image search. Proc Eur Conf Comp Vis Part I. 2008. p. 304-317. https:\/\/doi.org\/10.1007\/978-3-540-88682-2_24","DOI":"10.1007\/978-3-540-88682-2_24"},{"issue":"2","key":"10334_CR45","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1007\/s13042-022-01645-0","volume":"14","author":"G-H Liu","year":"2023","unstructured":"Liu G-H, Yang J-Y. Exploiting deep textures for image retrieval. Int J Mach Learn Cybern. 2023;14(2):483\u201394.","journal-title":"Int J Mach Learn Cybern"},{"key":"10334_CR46","doi-asserted-by":"publisher","first-page":"103909","DOI":"10.1016\/j.imavis.2020.103909","volume":"97","author":"JI Forc\u00e9n","year":"2020","unstructured":"Forc\u00e9n JI, Pagola M, Barrenechea E, Bustince H. Co-occurrence of deep convolutional features for image search. Image Vis Comput. 2020;97:103909.","journal-title":"Image Vis Comput"},{"issue":"3","key":"10334_CR47","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1007\/s13042-022-01654-z","volume":"14","author":"Z Lu","year":"2023","unstructured":"Lu Z, Liu G-H, Lu F, Zhang B-J. Image retrieval using dual-weighted deep feature descriptor. Int J Mach Learn Cybern. 2023;14(3):643\u201353.","journal-title":"Int J Mach Learn Cybern"},{"key":"10334_CR48","doi-asserted-by":"publisher","first-page":"110076","DOI":"10.1016\/j.patcog.2023.110076","volume":"147","author":"G-H Liu","year":"2024","unstructured":"Liu G-H, Li Z-Y, Yang J-Y, Zhang D. Exploiting sublimated deep features for image retrieval. Pattern Recogn. 2024;147:110076.","journal-title":"Pattern Recogn"},{"key":"10334_CR49","doi-asserted-by":"publisher","first-page":"102376","DOI":"10.1016\/j.displa.2023.102376","volume":"77","author":"K Liao","year":"2023","unstructured":"Liao K, Huang G, Zheng Y, Lin G, Cao C. Approximate object location deep visual representations for image retrieval. Displays. 2023;77:102376.","journal-title":"Displays"},{"key":"10334_CR50","doi-asserted-by":"publisher","unstructured":"Xu Y, Shamsolmoali P, Granger E, Nicodeme C, Gardes L, Yang J. TransVLAD: Multiscale attention-based global descriptors for visual geo-localization. In: IEEE\/CVF Winter Conference on Applications of Computer Vision, Waikoloa, HI, USA. 2023. p. 2839\u201348. https:\/\/doi.org\/10.1109\/WACV56688.2023.00286.","DOI":"10.1109\/WACV56688.2023.00286"}],"container-title":["Cognitive Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-024-10334-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12559-024-10334-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-024-10334-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T09:45:37Z","timestamp":1730972737000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12559-024-10334-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,27]]},"references-count":50,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["10334"],"URL":"https:\/\/doi.org\/10.1007\/s12559-024-10334-9","relation":{},"ISSN":["1866-9956","1866-9964"],"issn-type":[{"type":"print","value":"1866-9956"},{"type":"electronic","value":"1866-9964"}],"subject":[],"published":{"date-parts":[[2024,8,27]]},"assertion":[{"value":"18 September 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 July 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 August 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}]}}