{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T20:17:25Z","timestamp":1767212245761,"version":"3.37.3"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T00:00:00Z","timestamp":1683763200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T00:00:00Z","timestamp":1683763200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Natural Science Foundation of Chongqing, China","award":["No. cstc2019jcyj-zdxmX0011"],"award-info":[{"award-number":["No. cstc2019jcyj-zdxmX0011"]}]},{"name":"Chongqing Talent Plan","award":["Grant No.cstc2022ycjh-bgzxm0160"],"award-info":[{"award-number":["Grant No.cstc2022ycjh-bgzxm0160"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 62076044"],"award-info":[{"award-number":["No. 62076044"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chongqing Graduate Research Innovation Project of China","award":["No. CYS21307"],"award-info":[{"award-number":["No. CYS21307"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1007\/s13042-023-01842-5","type":"journal-article","created":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T09:57:02Z","timestamp":1683799022000},"page":"3437-3456","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Pseudo-label driven deep hashing for unsupervised cross-modal retrieval"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5892-2372","authenticated-orcid":false,"given":"XianHua","family":"Zeng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ke","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"YiCai","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,5,11]]},"reference":[{"key":"1842_CR1","unstructured":"Arthur D, Vassilvitskii S (2006) k-means++: the advantages of careful seeding. Tech. rep, Stanford"},{"key":"1842_CR2","doi-asserted-by":"crossref","unstructured":"Bronstein MM, Bronstein AM, Michel F et al (2010) Data fusion through cross-modality metric learning using similarity-sensitive hashing. In: 2010 IEEE computer society conference on computer vision and pattern recognition, IEEE, pp 3594\u20133601","DOI":"10.1109\/CVPR.2010.5539928"},{"key":"1842_CR3","doi-asserted-by":"crossref","unstructured":"Cao Y, Long M, Wang J et\u00a0al (2016) Correlation autoencoder hashing for supervised cross-modal search. In: Proceedings of the 2016 ACM on international conference on multimedia retrieval, pp 197\u2013204","DOI":"10.1145\/2911996.2912000"},{"key":"1842_CR4","doi-asserted-by":"crossref","unstructured":"Chua TS, Tang J, Hong R et\u00a0al (2009) Nus-wide: a real-world web image database from national university of Singapore. In: Proceedings of the ACM international conference on image and video retrieval, pp 1\u20139","DOI":"10.1145\/1646396.1646452"},{"key":"1842_CR5","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R et\u00a0al (2009) Imagenet: a large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition, Ieee, pp 248\u2013255","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"1842_CR6","doi-asserted-by":"crossref","unstructured":"Ding G, Guo Y, Zhou J (2014) Collective matrix factorization hashing for multimodal data. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2075\u20132082","DOI":"10.1109\/CVPR.2014.267"},{"issue":"10","key":"1842_CR7","doi-asserted-by":"publisher","first-page":"3023","DOI":"10.1007\/s13042-021-01395-5","volume":"12","author":"X Fang","year":"2021","unstructured":"Fang X, Liu Z, Han N et al (2021) Discrete matrix factorization hashing for cross-modal retrieval. Int J Mach Learn Cybern 12(10):3023\u20133036","journal-title":"Int J Mach Learn Cybern"},{"key":"1842_CR8","doi-asserted-by":"crossref","unstructured":"Feng F, Wang X, Li R (2014) Cross-modal retrieval with correspondence autoencoder. In: Proceedings of the 22nd ACM international conference on multimedia, pp 7\u201316","DOI":"10.1145\/2647868.2654902"},{"issue":"4","key":"1842_CR9","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1109\/TMM.2018.2866771","volume":"21","author":"D Hu","year":"2018","unstructured":"Hu D, Nie F, Li X (2018) Deep binary reconstruction for cross-modal hashing. IEEE Trans Multimedia 21(4):973\u2013985","journal-title":"IEEE Trans Multimedia"},{"key":"1842_CR10","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.knosys.2019.05.017","volume":"180","author":"P Hu","year":"2019","unstructured":"Hu P, Peng D, Wang X et al (2019) Multimodal adversarial network for cross-modal retrieval. Knowl-Based Syst 180:38\u201350","journal-title":"Knowl-Based Syst"},{"key":"1842_CR11","doi-asserted-by":"crossref","unstructured":"Huiskes MJ, Lew MS (2008) The mir flickr retrieval evaluation. In: Proceedings of the 1st ACM international conference on Multimedia information retrieval, pp 39\u201343","DOI":"10.1145\/1460096.1460104"},{"key":"1842_CR12","doi-asserted-by":"crossref","unstructured":"Jiang QY, Li WJ (2017) Deep cross-modal hashing. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3232\u20133240","DOI":"10.1109\/CVPR.2017.348"},{"issue":"3","key":"1842_CR13","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1109\/TMM.2015.2390499","volume":"17","author":"C Kang","year":"2015","unstructured":"Kang C, Xiang S, Liao S et al (2015) Learning consistent feature representation for cross-modal multimedia retrieval. IEEE Trans Multimedia 17(3):370\u2013381","journal-title":"IEEE Trans Multimedia"},{"key":"1842_CR14","unstructured":"Kumar S, Udupa R (2011) Learning hash functions for cross-view similarity search. In: Twenty-second international joint conference on artificial intelligence"},{"key":"1842_CR15","doi-asserted-by":"crossref","unstructured":"Li C, Deng C, Li N et al (2018) Self-supervised adversarial hashing networks for cross-modal retrieval. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4242\u20134251","DOI":"10.1109\/CVPR.2018.00446"},{"key":"1842_CR16","doi-asserted-by":"crossref","unstructured":"Li Y, Hu P, Liu Z et\u00a0al (2021) Contrastive clustering. In: Proceedings of the AAAI conference on artificial intelligence, pp 8547\u20138555","DOI":"10.1609\/aaai.v35i10.17037"},{"key":"1842_CR17","doi-asserted-by":"crossref","unstructured":"Lin Z, Ding G, Hu M et\u00a0al (2015) Semantics-preserving hashing for cross-view retrieval. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3864\u20133872","DOI":"10.1109\/CVPR.2015.7299011"},{"issue":"12","key":"1842_CR18","doi-asserted-by":"publisher","first-page":"4342","DOI":"10.1109\/TCYB.2016.2608906","volume":"47","author":"Z Lin","year":"2016","unstructured":"Lin Z, Ding G, Han J et al (2016) Cross-view retrieval via probability-based semantics-preserving hashing. IEEE Trans Cybern 47(12):4342\u20134355","journal-title":"IEEE Trans Cybern"},{"key":"1842_CR19","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1109\/TMM.2020.2984081","volume":"23","author":"Q Lin","year":"2020","unstructured":"Lin Q, Cao W, He Z et al (2020) Mask cross-modal hashing networks. IEEE Trans Multimedia 23:550\u2013558","journal-title":"IEEE Trans Multimedia"},{"key":"1842_CR20","doi-asserted-by":"crossref","unstructured":"Liu H, Lin M, Zhang S et\u00a0al (2018) Dense auto-encoder hashing for robust cross-modality retrieval. In: Proceedings of the 26th ACM international conference on multimedia, pp 1589\u20131597","DOI":"10.1145\/3240508.3240684"},{"key":"1842_CR21","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1016\/j.patcog.2019.05.008","volume":"93","author":"Y Liu","year":"2019","unstructured":"Liu Y, Guo Y, Liu L et al (2019) Cyclematch: a cycle-consistent embedding network for image-text matching. Pattern Recogn 93:365\u2013379","journal-title":"Pattern Recogn"},{"key":"1842_CR22","doi-asserted-by":"crossref","unstructured":"Liu S, Qian S, Guan Y et\u00a0al (2020) Joint-modal distribution-based similarity hashing for large-scale unsupervised deep cross-modal retrieval. In: Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval, pp 1379\u20131388","DOI":"10.1145\/3397271.3401086"},{"key":"1842_CR23","doi-asserted-by":"crossref","unstructured":"Lu X, Zhu L, Cheng Z et\u00a0al (2019a) Flexible online multi-modal hashing for large-scale multimedia retrieval. In: Proceedings of the 27th ACM international conference on multimedia, pp 1129\u20131137","DOI":"10.1145\/3343031.3350999"},{"key":"1842_CR24","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1016\/j.sigpro.2018.09.007","volume":"154","author":"X Lu","year":"2019","unstructured":"Lu X, Zhu L, Cheng Z et al (2019b) Efficient discrete latent semantic hashing for scalable cross-modal retrieval. Signal Process 154:217\u2013231","journal-title":"Signal Process"},{"issue":"3","key":"1842_CR25","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1109\/TPAMI.2013.142","volume":"36","author":"JC Pereira","year":"2013","unstructured":"Pereira JC, Coviello E, Doyle G et al (2013) On the role of correlation and abstraction in cross-modal multimedia retrieval. IEEE Trans Pattern Anal Mach Intell 36(3):521\u2013535","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1842_CR26","doi-asserted-by":"crossref","unstructured":"Rasiwasia N, Costa\u00a0Pereira J, Coviello E et\u00a0al (2010) A new approach to cross-modal multimedia retrieval. In: Proceedings of the 18th ACM international conference on multimedia, pp 251\u2013260","DOI":"10.1145\/1873951.1873987"},{"key":"1842_CR27","unstructured":"Ruder S (2016) An overview of gradient descent optimization algorithms. arXiv preprint arXiv:1609.04747"},{"key":"1842_CR28","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556"},{"key":"1842_CR29","doi-asserted-by":"crossref","unstructured":"Song J, Yang Y, Yang Y et\u00a0al (2013) Inter-media hashing for large-scale retrieval from heterogeneous data sources. In: Proceedings of the 2013 ACM SIGMOD international conference on management of data, pp 785\u2013796","DOI":"10.1145\/2463676.2465274"},{"key":"1842_CR30","doi-asserted-by":"crossref","unstructured":"Su S, Zhong Z, Zhang C (2019) Deep joint-semantics reconstructing hashing for large-scale unsupervised cross-modal retrieval. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 3027\u20133035","DOI":"10.1109\/ICCV.2019.00312"},{"key":"1842_CR31","doi-asserted-by":"crossref","unstructured":"Wang B, Yang Y, Xu X et\u00a0al (2017) Adversarial cross-modal retrieval. In: Proceedings of the 25th ACM international conference on Multimedia, pp 154\u2013162","DOI":"10.1145\/3123266.3123326"},{"key":"1842_CR32","unstructured":"Weiss Y, Torralba A, Fergus R (2008) Spectral hashing. Adv Neural Inf Process Syst 21"},{"key":"1842_CR33","unstructured":"Wu B, Yang Q, Zheng WS et\u00a0al (2015a) Quantized correlation hashing for fast cross-modal search. In: Twenty-fourth international joint conference on artificial intelligence"},{"issue":"5","key":"1842_CR34","doi-asserted-by":"publisher","first-page":"1497","DOI":"10.1109\/TIP.2015.2403240","volume":"24","author":"F Wu","year":"2015","unstructured":"Wu F, Jiang X, Li X et al (2015b) Cross-modal learning to rank via latent joint representation. IEEE Trans Image Process 24(5):1497\u20131509","journal-title":"IEEE Trans Image Process"},{"key":"1842_CR35","doi-asserted-by":"crossref","unstructured":"Wu G, Lin Z, Han J et\u00a0al (2018) Unsupervised deep hashing via binary latent factor models for large-scale cross-modal retrieval. In: IJCAI, p\u00a05","DOI":"10.24963\/ijcai.2018\/396"},{"key":"1842_CR36","doi-asserted-by":"publisher","first-page":"3626","DOI":"10.1109\/TIP.2020.2963957","volume":"29","author":"D Xie","year":"2020","unstructured":"Xie D, Deng C, Li C et al (2020) Multi-task consistency-preserving adversarial hashing for cross-modal retrieval. IEEE Trans Image Process 29:3626\u20133637","journal-title":"IEEE Trans Image Process"},{"issue":"5","key":"1842_CR37","doi-asserted-by":"publisher","first-page":"2494","DOI":"10.1109\/TIP.2017.2676345","volume":"26","author":"X Xu","year":"2017","unstructured":"Xu X, Shen F, Yang Y et al (2017) Learning discriminative binary codes for large-scale cross-modal retrieval. IEEE Trans Image Process 26(5):2494\u20132507","journal-title":"IEEE Trans Image Process"},{"key":"1842_CR40","doi-asserted-by":"crossref","unstructured":"Yang D, Wu D, Zhang W et\u00a0al (2020) Deep semantic-alignment hashing for unsupervised cross-modal retrieval. In: Proceedings of the 2020 international conference on multimedia retrieval, pp 44\u201352","DOI":"10.1145\/3372278.3390673"},{"key":"1842_CR38","doi-asserted-by":"crossref","unstructured":"Yang F, Ding X, Liu Y et\u00a0al (2022a) Scalable semantic-enhanced supervised hashing for cross-modal retrieval. Knowl-Based Syst:109176","DOI":"10.1016\/j.knosys.2022.109176"},{"key":"1842_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108823","volume":"130","author":"F Yang","year":"2022","unstructured":"Yang F, Liu Y, Ding X et al (2022b) Asymmetric cross-modal hashing with high-level semantic similarity. Pattern Recogn 130:108823","journal-title":"Pattern Recogn"},{"key":"1842_CR41","doi-asserted-by":"crossref","unstructured":"Ye Z, Peng Y (2018) Multi-scale correlation for sequential cross-modal hashing learning. In: Proceedings of the 26th ACM international conference on Multimedia, pp 852\u2013860","DOI":"10.1145\/3240508.3240560"},{"key":"1842_CR42","doi-asserted-by":"crossref","unstructured":"Yu J, Zhou H, Zhan Y et\u00a0al (2021) Deep graph-neighbor coherence preserving network for unsupervised cross-modal hashing. In: Proceedings of the AAAI conference on artificial intelligence, pp 4626\u20134634","DOI":"10.1609\/aaai.v35i5.16592"},{"key":"1842_CR43","doi-asserted-by":"crossref","unstructured":"Zhang D, Li WJ (2014) Large-scale supervised multimodal hashing with semantic correlation maximization. In: Proceedings of the AAAI conference on artificial intelligence","DOI":"10.1609\/aaai.v28i1.8995"},{"key":"1842_CR44","doi-asserted-by":"crossref","unstructured":"Zhang J, Peng Y, Yuan M (2018) Unsupervised generative adversarial cross-modal hashing. In: Proceedings of the AAAI conference on artificial intelligence","DOI":"10.1609\/aaai.v32i1.11263"},{"issue":"4","key":"1842_CR45","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1007\/s13042-019-00962-1","volume":"11","author":"W Zheng","year":"2020","unstructured":"Zheng W, Liu H, Wang B et al (2020) Cross-modal learning for material perception using deep extreme learning machine. Int J Mach Learn Cybern 11(4):813\u2013823","journal-title":"Int J Mach Learn Cybern"},{"key":"1842_CR46","doi-asserted-by":"crossref","unstructured":"Zhou J, Ding G, Guo Y (2014) Latent semantic sparse hashing for cross-modal similarity search. In: Proceedings of the 37th international ACM SIGIR conference on research & development in information retrieval, pp 415\u2013424","DOI":"10.1145\/2600428.2609610"},{"key":"1842_CR47","doi-asserted-by":"crossref","unstructured":"Zhu X, Huang Z, Shen HT et\u00a0al (2013) Linear cross-modal hashing for efficient multimedia search. In: Proceedings of the 21st ACM international conference on multimedia, pp 143\u2013152","DOI":"10.1145\/2502081.2502107"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-01842-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-023-01842-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-01842-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T05:28:06Z","timestamp":1692682086000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-023-01842-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,11]]},"references-count":47,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["1842"],"URL":"https:\/\/doi.org\/10.1007\/s13042-023-01842-5","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2023,5,11]]},"assertion":[{"value":"19 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 April 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 May 2023","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 that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}