{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T03:14:42Z","timestamp":1774235682122,"version":"3.50.1"},"reference-count":110,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T00:00:00Z","timestamp":1653868800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T00:00:00Z","timestamp":1653868800000},"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":["Vis Comput"],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1007\/s00371-022-02470-w","type":"journal-article","created":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T13:04:52Z","timestamp":1653915892000},"page":"2149-2163","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A study on zero-shot learning from semantic viewpoint"],"prefix":"10.1007","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5134-4477","authenticated-orcid":false,"given":"P K","family":"Bhagat","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prakash","family":"Choudhary","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kh Manglem","family":"Singh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,5,30]]},"reference":[{"key":"2470_CR1","doi-asserted-by":"publisher","unstructured":"Akata, Z., Malinowski, M., Fritz, M., Schiele, B.: Multi-cue zero-shot learning with strong supervision. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 59\u201368 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.14","DOI":"10.1109\/CVPR.2016.14"},{"key":"2470_CR2","doi-asserted-by":"publisher","unstructured":"Akata, Z., Perronnin, F., Harchaoui, Z., Schmid, C.: Label-embedding for attribute-based classification. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp. 819\u2013826 (2013). https:\/\/doi.org\/10.1109\/CVPR.2013.111","DOI":"10.1109\/CVPR.2013.111"},{"issue":"7","key":"2470_CR3","doi-asserted-by":"publisher","first-page":"1425","DOI":"10.1109\/TPAMI.2015.2487986","volume":"38","author":"Z Akata","year":"2016","unstructured":"Akata, Z., Perronnin, F., Harchaoui, Z., Schmid, C.: Label-embedding for image classification. IEEE Trans. Pattern Anal. Mach. Intell. 38(7), 1425\u20131438 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2470_CR4","doi-asserted-by":"crossref","unstructured":"Akata, Z., Reed, S., Walter, D., , Schiele, B.: Evaluation of output embeddings for fine-grained image classification. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2927\u20132936 (2015)","DOI":"10.1109\/CVPR.2015.7298911"},{"key":"2470_CR5","doi-asserted-by":"publisher","unstructured":"Al-Halah, Z., Stiefelhagen, R.: How to transfer? zero-shot object recognition via hierarchical transfer of semantic attributes. In: 2015 IEEE Winter Conference on Applications of Computer Vision, pp. 837\u2013843 (2015). https:\/\/doi.org\/10.1109\/WACV.2015.116","DOI":"10.1109\/WACV.2015.116"},{"key":"2470_CR6","doi-asserted-by":"crossref","unstructured":"An, F.P., Liu, J.e., Bai, L.: Object recognition algorithm based on optimized nonlinear activation function-global convolutional neural network. Vis. Comput. pp. 1\u201313 (2021)","DOI":"10.1007\/s00371-020-02033-x"},{"key":"2470_CR7","doi-asserted-by":"crossref","unstructured":"Ba, J.L., Swersky, K., Fidler, S., Salakhutdinov, R.: Predicting deep zero-shot convolutional neural networks using textual descriptions. In: 2015 IEEE International Conference on Computer Vision (ICCV), pp. 4247\u20134255 (2015)","DOI":"10.1109\/ICCV.2015.483"},{"key":"2470_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.imavis.2018.09.017","volume":"80","author":"PK Bhagat","year":"2018","unstructured":"Bhagat, P.K., Choudhary, P.: Image annotation: then and now. Image Vis. Comput. 80, 1\u201323 (2018)","journal-title":"Image Vis. Comput."},{"key":"2470_CR9","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-02615-6","author":"PK Bhagat","year":"2021","unstructured":"Bhagat, P.K., Choudhary, P., Singh, K.M.: A novel approach based on fully connected weighted bipartite graph for zero-shot learning problems. J. Ambient. Intell. Humaniz. Comput. (2021). https:\/\/doi.org\/10.1007\/s12652-020-02615-6","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"issue":"5527","key":"2470_CR10","doi-asserted-by":"publisher","first-page":"582","DOI":"10.1038\/257582a0","volume":"257","author":"DR Bradley","year":"1975","unstructured":"Bradley, D.R., Dumais, S.T.: Ambiguous cognitive contours. Nature 257(5527), 582\u2013584 (1975). https:\/\/doi.org\/10.1038\/257582a0","journal-title":"Nature"},{"key":"2470_CR11","doi-asserted-by":"publisher","unstructured":"Changpinyo, S., Chao, W., Gong, B., Sha, F.: Synthesized classifiers for zero-shot learning. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5327\u20135336 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.575","DOI":"10.1109\/CVPR.2016.575"},{"key":"2470_CR12","doi-asserted-by":"crossref","unstructured":"Chao, W.L., Changpinyo, S., Gong, B., Sha, F.: An empirical study and analysis of generalized zero-shot learning for object recognition in the wild. In: European Conference on Computer Vision, pp. 52\u201368. Springer (2016)","DOI":"10.1007\/978-3-319-46475-6_4"},{"key":"2470_CR13","doi-asserted-by":"publisher","unstructured":"Cheng, H.T., Sun, F.T., Griss, M., Davis, P., Li, J., You, D.: Nuactiv: Recognizing unseen new activities using semantic attribute-based learning. In: Proceeding of the 11th Annual International Conference on Mobile Systems, Applications, and Services, pp. 361\u2013374. Association for Computing Machinery, New York, NY, USA (2013). https:\/\/doi.org\/10.1145\/2462456.2464438","DOI":"10.1145\/2462456.2464438"},{"issue":"2","key":"2470_CR14","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1207\/s15516709cog1402_1","volume":"14","author":"JL Elman","year":"1990","unstructured":"Elman, J.L.: Finding structure in time. Cogn. Sci. 14(2), 179\u2013211 (1990)","journal-title":"Cogn. Sci."},{"key":"2470_CR15","doi-asserted-by":"crossref","unstructured":"Farhadi, A., Endres, I., Hoiem, D., Forsyth, D.: Describing objects by their attributes. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1778\u20131785 (2009)","DOI":"10.1109\/CVPR.2009.5206772"},{"key":"2470_CR16","doi-asserted-by":"publisher","unstructured":"Feng, J., Jegelka, S., Yan, S., Darrell, T.: Learning scalable discriminative dictionary with sample relatedness. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1645\u20131652 (2014). https:\/\/doi.org\/10.1109\/CVPR.2014.213","DOI":"10.1109\/CVPR.2014.213"},{"key":"2470_CR17","unstructured":"Forsyth, D.A., Ponce, J.: Computer Vision: A Modern Approach, Second Edition. Pitman (2012)"},{"key":"2470_CR18","unstructured":"Frome, A., Corrado, G.S., Shlens, J., Bengio, S., Dean, J., Ranzato, M.A., Mikolov, T.: Devise: A deep visual-semantic embedding model. In: C.J.C. Burges, L.\u00a0Bottou, M.\u00a0Welling, Z.\u00a0Ghahramani, K.Q. Weinberger (eds.) Advances in Neural Information Processing Systems, Vol. 26, pp. 2121\u20132129. Curran Associates, Inc. (2013)"},{"key":"2470_CR19","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1007\/978-3-642-33765-9_38","volume-title":"Computer Vision - ECCV 2012","author":"Y Fu","year":"2012","unstructured":"Fu, Y., Hospedales, T.M., Xiang, T., Gong, S.: Attribute learning for understanding unstructured social activity. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) Computer Vision - ECCV 2012, pp. 530\u2013543. Springer, Berlin (2012)"},{"issue":"2","key":"2470_CR20","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1109\/TPAMI.2013.128","volume":"36","author":"Y Fu","year":"2014","unstructured":"Fu, Y., Hospedales, T.M., Xiang, T., Gong, S.: Learning multimodal latent attributes. IEEE Trans. Pattern Anal. Mach. Intell. 36(2), 303\u2013316 (2014). https:\/\/doi.org\/10.1109\/TPAMI.2013.128","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"12","key":"2470_CR21","doi-asserted-by":"publisher","first-page":"3136","DOI":"10.1109\/TPAMI.2019.2922175","volume":"42","author":"Y Fu","year":"2020","unstructured":"Fu, Y., Wang, X., Dong, H., Jiang, Y.G., Wang, M., Xue, X., Sigal, L.: Vocabulary-informed zero-shot and open-set learning. IEEE Trans. Pattern Anal. Mach. Intell. 42(12), 3136\u20133152 (2020). https:\/\/doi.org\/10.1109\/TPAMI.2019.2922175","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"2470_CR22","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/MSP.2017.2763441","volume":"35","author":"Y Fu","year":"2018","unstructured":"Fu, Y., Xiang, T., Jiang, Y., Xue, X., Sigal, L., Gong, S.: Recent advances in zero-shot recognition: Toward data-efficient understanding of visual content. IEEE Signal Process. Mag. 35(1), 112\u2013125 (2018). https:\/\/doi.org\/10.1109\/MSP.2017.2763441","journal-title":"IEEE Signal Process. Mag."},{"issue":"8","key":"2470_CR23","doi-asserted-by":"publisher","first-page":"2009","DOI":"10.1109\/TPAMI.2017.2737007","volume":"40","author":"Z Fu","year":"2017","unstructured":"Fu, Z., Xiang, T., Kodirov, E., Gong, S.: Zero-shot learning on semantic class prototype graph. IEEE Trans. Pattern Anal. Mach. Intell. 40(8), 2009\u20132022 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2470_CR24","doi-asserted-by":"crossref","unstructured":"Gan, C., Yang, T., Gong, B.: Learning attributes equals multi-source domain generalization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 87\u201397 (2016)","DOI":"10.1109\/CVPR.2016.17"},{"key":"2470_CR25","doi-asserted-by":"publisher","unstructured":"Gan, C., Yang, T., Gong, B.: Learning attributes equals multi-source domain generalization. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 87\u201397 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.17","DOI":"10.1109\/CVPR.2016.17"},{"key":"2470_CR26","doi-asserted-by":"crossref","unstructured":"Gao, L., Song, J., Shao, J., Zhu, X., Shen, H.: Zero-shot image categorization by image correlation exploration. In: Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, pp. 487\u2013490 (2015)","DOI":"10.1145\/2671188.2749309"},{"key":"2470_CR27","volume-title":"Digital Image Processing","author":"RC Gonzalez","year":"2001","unstructured":"Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Addison-Wesley Longman Publishing Co., New York (2001)","edition":"2"},{"key":"2470_CR28","doi-asserted-by":"crossref","unstructured":"Guo, Y., Ding, G., Jin, X., Wang, J.: Transductive zero-shot recognition via shared model space learning. In: AAAI (2016)","DOI":"10.1609\/aaai.v30i1.10448"},{"key":"2470_CR29","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"2470_CR30","doi-asserted-by":"publisher","unstructured":"Huang, S., Elhoseiny, M., Elgammal, A., Yang, D.: Learning hypergraph-regularized attribute predictors. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 409\u2013417 (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7298638","DOI":"10.1109\/CVPR.2015.7298638"},{"key":"2470_CR31","doi-asserted-by":"publisher","unstructured":"Jayaraman, D., Sha, F., Grauman, K.: Decorrelating semantic visual attributes by resisting the urge to share. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1629\u20131636 (2014). https:\/\/doi.org\/10.1109\/CVPR.2014.211","DOI":"10.1109\/CVPR.2014.211"},{"key":"2470_CR32","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.neunet.2021.05.019","volume":"143","author":"Z Ji","year":"2021","unstructured":"Ji, Z., Wang, Q., Cui, B., Pang, Y., Cao, X., Li, X.: A semi-supervised zero-shot image classification method based on soft-target. Neural Netw. 143, 88\u201396 (2021). https:\/\/doi.org\/10.1016\/j.neunet.2021.05.019","journal-title":"Neural Netw."},{"key":"2470_CR33","doi-asserted-by":"publisher","first-page":"1958","DOI":"10.1109\/TIP.2019.2947780","volume":"29","author":"Z Jia","year":"2020","unstructured":"Jia, Z., Zhang, Z., Wang, L., Shan, C., Tan, T.: Deep unbiased embedding transfer for zero-shot learning. IEEE Trans. Image Process. 29, 1958\u20131971 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"2470_CR34","doi-asserted-by":"publisher","unstructured":"Jiang, H., Wang, R., Shan, S., Yang, Y., Chen, X.: Learning discriminative latent attributes for zero-shot classification. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 4233\u20134242 (2017). https:\/\/doi.org\/10.1109\/ICCV.2017.453","DOI":"10.1109\/ICCV.2017.453"},{"key":"2470_CR35","doi-asserted-by":"publisher","unstructured":"Jurie, F., Bucher, M., Herbin, S.: Generating visual representations for zero-shot classification. In: 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), pp. 2666\u20132673 (2017). https:\/\/doi.org\/10.1109\/ICCVW.2017.308","DOI":"10.1109\/ICCVW.2017.308"},{"key":"2470_CR36","unstructured":"Kemp, C., Tenenbaum, J.B., Griffiths, T.L., Yamada, T., Ueda, N.: Learning systems of concepts with an infinite relational model. In: Proceedings of the 21st National Conference on Artificial Intelligence - Volume 1, AAAI\u201906, pp. 381\u2013388. AAAI Press (2006)"},{"key":"2470_CR37","doi-asserted-by":"publisher","unstructured":"Kodirov, E., Xiang, T., Gong, S.: Semantic autoencoder for zero-shot learning. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4447\u20134456 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.473","DOI":"10.1109\/CVPR.2017.473"},{"key":"2470_CR38","doi-asserted-by":"crossref","unstructured":"Kordumova, S., Mensink, T., Snoek, C.G.: Pooling objects for recognizing scenes without examples. In: Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval, pp. 143\u2013150 (2016)","DOI":"10.1145\/2911996.2912007"},{"key":"2470_CR39","doi-asserted-by":"publisher","unstructured":"Lampert, C.H., Nickisch, H., Harmeling, S.: Learning to detect unseen object classes by between-class attribute transfer. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 951\u2013958 (2009). https:\/\/doi.org\/10.1109\/CVPR.2009.5206594","DOI":"10.1109\/CVPR.2009.5206594"},{"issue":"3","key":"2470_CR40","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1109\/TPAMI.2013.140","volume":"36","author":"CH Lampert","year":"2014","unstructured":"Lampert, C.H., Nickisch, H., Harmeling, S.: Attribute-based classification for zero-shot visual object categorization. IEEE Trans. Pattern Anal. Mach. Intell. 36(3), 453\u2013465 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2470_CR41","doi-asserted-by":"crossref","unstructured":"Lazaridou, A., Dinu, G., Baroni, M.: Hubness and pollution: Delving into cross-space mapping for zero-shot learning. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 270\u2013280 (2015)","DOI":"10.3115\/v1\/P15-1027"},{"key":"2470_CR42","doi-asserted-by":"crossref","unstructured":"Li, H., Li, D., Luo, X.: Bap: Bimodal attribute prediction for zero-shot image categorization. Proceedings of the 22nd ACM International Conference on Multimedia (2014)","DOI":"10.1145\/2647868.2655023"},{"key":"2470_CR43","unstructured":"Li, X., Guo, Y.: Max-Margin Zero-Shot Learning for Multi-class Classification. In: Lebanon, G., Vishwanathan, S. V. N. (eds.) Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research, pp. 626\u2013634. PMLR, San Diego, California, USA (2015) http:\/\/proceedings.mlr.press\/v38\/li15d.html"},{"key":"2470_CR44","doi-asserted-by":"publisher","unstructured":"Li, X., Liao, S., Lan, W., Du, X., Yang, G.: Zero-shot image tagging by hierarchical semantic embedding. In: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR \u201915, pp. 879\u2013882. Association for Computing Machinery, New York, NY, USA (2015). https:\/\/doi.org\/10.1145\/2766462.2767773","DOI":"10.1145\/2766462.2767773"},{"key":"2470_CR45","doi-asserted-by":"crossref","unstructured":"Li, Y., Jia, Z., Zhang, J., Huang, K., Tan, T.: Deep semantic structural constraints for zero-shot learning. In: AAAI (2018)","DOI":"10.1609\/aaai.v32i1.12244"},{"key":"2470_CR46","doi-asserted-by":"publisher","unstructured":"Li, Y., Wang, D., Hu, H., Lin, Y., Zhuang, Y.: Zero-shot recognition using dual visual-semantic mapping paths. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp, 5207\u20135215 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.553","DOI":"10.1109\/CVPR.2017.553"},{"key":"2470_CR47","doi-asserted-by":"publisher","unstructured":"Li, Y., Zhang, J., Zhang, J., Huang, K.: Discriminative learning of latent features for zero-shot recognition. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7463\u20137471 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00779","DOI":"10.1109\/CVPR.2018.00779"},{"key":"2470_CR48","doi-asserted-by":"publisher","unstructured":"Liang, K., Chang, H., Shan, S., Chen, X.: A unified multiplicative framework for attribute learning. In: 2015 IEEE International Conference on Computer Vision (ICCV), pp. 2506\u20132514 (2015). https:\/\/doi.org\/10.1109\/ICCV.2015.288","DOI":"10.1109\/ICCV.2015.288"},{"key":"2470_CR49","doi-asserted-by":"publisher","unstructured":"Long, Y., Liu, L., Shao, L., Shen, F., Ding, G., Han, J.: From zero-shot learning to conventional supervised classification: Unseen visual data synthesis. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6165\u20136174 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.653","DOI":"10.1109\/CVPR.2017.653"},{"key":"2470_CR50","doi-asserted-by":"crossref","unstructured":"Mensink, T., Verbeek, J., Perronnin, F., Csurka, G.: Metric learning for large scale image classification: Generalizing to new classes at near-zero cost. In: European Conference on Computer Vision, pp. 488\u2013501. Springer (2012)","DOI":"10.1007\/978-3-642-33709-3_35"},{"key":"2470_CR51","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. In: Y.\u00a0Bengio, Y.\u00a0LeCun (eds.) 1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2-4, 2013, Workshop Track Proceedings (2013)"},{"key":"2470_CR52","doi-asserted-by":"crossref","unstructured":"Mikolov, T., Kopecky, J., Burget, L., Glembek, O., ?Cernocky, J.: Neural network based language models for highly inflective languages. In: 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 4725\u20134728 (2009)","DOI":"10.1109\/ICASSP.2009.4960686"},{"key":"2470_CR53","unstructured":"Mikolov, T., Yih, W.t., Zweig, G.: Linguistic regularities in continuous space word representations. In: Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746\u2013751. Association for Computational Linguistics, Atlanta, Georgia (2013)"},{"issue":"11","key":"2470_CR54","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1145\/219717.219748","volume":"38","author":"G A Miller","year":"1995","unstructured":"Miller, G. A.: Wordnet: A lexical database for english. Commun. ACM 38(11), 39\u201341 (1995). https:\/\/doi.org\/10.1145\/219717.219748","journal-title":"Commun. ACM"},{"key":"2470_CR55","doi-asserted-by":"publisher","unstructured":"Morgado, P., Vasconcelos, N.: Semantically consistent regularization for zero-shot recognition. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2037\u20132046 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.220","DOI":"10.1109\/CVPR.2017.220"},{"key":"2470_CR56","doi-asserted-by":"crossref","unstructured":"Narayan, S., Gupta, A., Khan, F.S., Snoek, C.G., Shao, L.: Latent embedding feedback and discriminative features for zero-shot classification. In: ECCV (2020)","DOI":"10.1007\/978-3-030-58542-6_29"},{"key":"2470_CR57","unstructured":"Norouzi, M., Mikolov, T., Bengio, S., Singer, Y., Shlens, J., Frome, A., Corrado, G., Dean, J.: Zero-shot learning by convex combination of semantic embeddings. In: International Conference on Learning Representations (2014). http:\/\/arxiv.org\/abs\/1312.5650"},{"issue":"2","key":"2470_CR58","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1207\/s15516709cog1502_3","volume":"15","author":"DN Osherson","year":"1991","unstructured":"Osherson, D.N., Stern, J., Wilkie, O., Stob, M., Smith, E.E.: Default probability. Cogn. Sci. 15(2), 251\u2013269 (1991)","journal-title":"Cogn. Sci."},{"key":"2470_CR59","unstructured":"Palatucci, M., Pomerleau, D., Hinton, G., Mitchell, T.M.: Zero-shot learning with semantic output codes. In: Proceedings of the 22Nd International Conference on Neural Information Processing Systems, NIPS\u201909, pp. 1410\u20131418. Curran Associates Inc., USA (2009)"},{"key":"2470_CR60","doi-asserted-by":"publisher","unstructured":"Pambala, A.K., Dutta, T., Biswas, S.: Generative model with semantic embedding and integrated classifier for generalized zero-shot learning. In: 2020 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1226\u20131235 (2020). https:\/\/doi.org\/10.1109\/WACV45572.2020.9093625","DOI":"10.1109\/WACV45572.2020.9093625"},{"issue":"3","key":"2470_CR61","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1023\/A:1014080923068","volume":"46","author":"N Paragios","year":"2002","unstructured":"Paragios, N., Deriche, R.: Geodesic active regions and level set methods for supervised texture segmentation. Int. J. Comput. Vis. 46(3), 223\u2013247 (2002)","journal-title":"Int. J. Comput. Vis."},{"key":"2470_CR62","doi-asserted-by":"publisher","unstructured":"Parikh, D., Grauman, K.: Relative attributes. In: Proceedings of the 2011 International Conference on Computer Vision, ICCV \u201911, pp. 503\u2013510. IEEE Computer Society, USA (2011). https:\/\/doi.org\/10.1109\/ICCV.2011.6126281","DOI":"10.1109\/ICCV.2011.6126281"},{"key":"2470_CR63","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0810966105","author":"L Parkkonen","year":"2008","unstructured":"Parkkonen, L., Andersson, J., H\u00e4m\u00e4l\u00e4inen, M., Hari, R.: Early visual brain areas reflect the percept of an ambiguous scene. Proc. Natl. Acad. Sci. (2008). https:\/\/doi.org\/10.1073\/pnas.0810966105","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"7","key":"2470_CR64","doi-asserted-by":"publisher","first-page":"1625","DOI":"10.1109\/TPAMI.2017.2723882","volume":"40","author":"P Peng","year":"2018","unstructured":"Peng, P., Tian, Y., Xiang, T., Wang, Y., Pontil, M., Huang, T.: Joint semantic and latent attribute modelling for cross-class transfer learning. IEEE Trans. Pattern Anal. Mach. Intell. 40(7), 1625\u20131638 (2018). https:\/\/doi.org\/10.1109\/TPAMI.2017.2723882","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2470_CR65","doi-asserted-by":"publisher","unstructured":"Pennington, J., Socher, R., Manning, C.: GloVe: Global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543. Association for Computational Linguistics, Doha, Qatar (2014).https:\/\/doi.org\/10.3115\/v1\/D14-1162","DOI":"10.3115\/v1\/D14-1162"},{"key":"2470_CR66","doi-asserted-by":"publisher","unstructured":"Pi, T., Li, X., Zhang, Z.M.: Boosted zero-shot learning with semantic correlation regularization. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17, pp. 2599\u20132605 (2017). https:\/\/doi.org\/10.24963\/ijcai.2017\/362","DOI":"10.24963\/ijcai.2017\/362"},{"issue":"2","key":"2470_CR67","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1007\/s00371-020-02046-6","volume":"38","author":"K Qian","year":"2022","unstructured":"Qian, K., Wen, X., Song, A.: Hybrid neural network model for large-scale heterogeneous classification tasks in few-shot learning. Vis. Comput. 38(2), 719\u2013728 (2022). https:\/\/doi.org\/10.1007\/s00371-020-02046-6","journal-title":"Vis. Comput."},{"key":"2470_CR68","doi-asserted-by":"publisher","unstructured":"Qiao, R., Liu, L., Shen, C., Van Den Hengel, A.: Less is more: Zero-shot learning from online textual documents with noise suppression. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2249\u20132257 (2016).https:\/\/doi.org\/10.1109\/CVPR.2016.247","DOI":"10.1109\/CVPR.2016.247"},{"issue":"4","key":"2470_CR69","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1109\/TPAMI.2006.79","volume":"28","author":"R Fergus","year":"2006","unstructured":"Fergus, R., Perona, P.: One-shot learning of object categories. IEEE Trans. Pattern Anal. Mach. Intell. 28(4), 594\u2013611 (2006)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2470_CR70","doi-asserted-by":"publisher","first-page":"876","DOI":"10.1007\/978-3-642-33783-3_63","volume-title":"Computer Vision - ECCV 2012","author":"M Rastegari","year":"2012","unstructured":"Rastegari, M., Farhadi, A., Forsyth, D.: Attribute discovery via predictable discriminative binary codes. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) Computer Vision - ECCV 2012, pp. 876\u2013889. Springer, Berlin (2012)"},{"key":"2470_CR71","unstructured":"Ravi, S., Larochelle, H.: Optimization as a model for few-shot learning. In: Proceedings of 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017 (2017)"},{"key":"2470_CR72","doi-asserted-by":"publisher","unstructured":"Reed, S., Akata, Z., Lee, H., Schiele, B.: Learning deep representations of fine-grained visual descriptions. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 49\u201358 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.13","DOI":"10.1109\/CVPR.2016.13"},{"issue":"1","key":"2470_CR73","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1002\/vis.4340010106","volume":"1","author":"O Renault","year":"1990","unstructured":"Renault, O., Thalmann, N.M., Thalmann, D.: A vision-based approach to behavioural animation. J. Vis. Comput. Animat. 1(1), 18\u201321 (1990). https:\/\/doi.org\/10.1002\/vis.4340010106","journal-title":"J. Vis. Comput. Animat."},{"key":"2470_CR74","doi-asserted-by":"publisher","first-page":"808","DOI":"10.1007\/978-3-642-33783-3_58","volume-title":"Computer Vision - ECCV 2012","author":"S Rifai","year":"2012","unstructured":"Rifai, S., Bengio, Y., Courville, A., Vincent, P., Mirza, M.: Disentangling factors of variation for facial expression recognition. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) Computer Vision - ECCV 2012, pp. 808\u2013822. Springer, Berlin (2012)"},{"key":"2470_CR75","unstructured":"Rohrbach, M., Ebert, S., Schiele, B.: Transfer learning in a transductive setting. In: Proceedings of the 26th International Conference on Neural Information Processing Systems - Volume 1, NIPS\u201913, pp. 46\u201354. Curran Associates Inc., Red Hook, NY, USA (2013)"},{"key":"2470_CR76","doi-asserted-by":"crossref","unstructured":"Rohrbach, M., Stark, M., Schiele, B.: Evaluating knowledge transfer and zero-shot learning in a large-scale setting. In: CVPR 2011, pp. 1641\u20131648 (2011)","DOI":"10.1109\/CVPR.2011.5995627"},{"key":"2470_CR77","doi-asserted-by":"crossref","unstructured":"Rohrbach, M., Stark, M., Szarvas, G., Gurevych, I., Schiele, B.: What helps where\u2013and why? semantic relatedness for knowledge transfer. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 910\u2013917. IEEE (2010)","DOI":"10.1109\/CVPR.2010.5540121"},{"key":"2470_CR78","unstructured":"Romera-Paredes, B., Torr, P.: An embarrassingly simple approach to zero-shot learning. In: International Conference on Machine Learning, pp. 2152\u20132161 (2015)"},{"key":"2470_CR79","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Parallel distributed processing: Explorations in the microstructure of cognition, vol. 1. chap. Learning Internal Representations by Error Propagation, pp. 318\u2013362. MIT Press, Cambridge, MA, USA (1986)"},{"key":"2470_CR80","doi-asserted-by":"crossref","unstructured":"Sariyildiz, M.B., Cinbis, R.G.: Gradient matching generative networks for zero-shot learning. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2163\u20132173 (2019)","DOI":"10.1109\/CVPR.2019.00227"},{"key":"2470_CR81","doi-asserted-by":"crossref","unstructured":"Schuldt, C., Laptev, I., Caputo, B.: Recognizing human actions: A local svm approach. In: Proceedings of the Pattern Recognition, 17th International Conference on (ICPR\u201904) Volume 3 - Volume 03, ICPR \u201904, pp. 32\u201336. IEEE Computer Society, Washington, DC, USA (2004)","DOI":"10.1109\/ICPR.2004.1334462"},{"key":"2470_CR82","doi-asserted-by":"publisher","unstructured":"Sch\u00f6nfeld, E., Ebrahimi, S., Sinha, S., Darrell, T., Akata, Z.: Generalized zero- and few-shot learning via aligned variational autoencoders. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8239\u20138247 (2019).https:\/\/doi.org\/10.1109\/CVPR.2019.00844","DOI":"10.1109\/CVPR.2019.00844"},{"issue":"22","key":"2470_CR83","doi-asserted-by":"publisher","first-page":"12340","DOI":"10.1073\/pnas.221383698","volume":"98","author":"S Shimojo","year":"2001","unstructured":"Shimojo, S., Paradiso, M., Fujita, I.: What visual perception tells us about mind and brain. Proc. Natl. Acad. Sci. 98(22), 12340\u201312341 (2001). https:\/\/doi.org\/10.1073\/pnas.221383698","journal-title":"Proc. Natl. Acad. Sci."},{"key":"2470_CR84","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/978-3-642-33709-3_6","volume-title":"Computer Vision - ECCV 2012","author":"S Singh","year":"2012","unstructured":"Singh, S., Gupta, A., Efros, A.A.: Unsupervised discovery of mid-level discriminative patches. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) Computer Vision - ECCV 2012, pp. 73\u201386. Springer, Berlin (2012)"},{"key":"2470_CR85","unstructured":"Socher, R., Ganjoo, M., Manning, C.D., Ng, A.: Zero-shot learning through cross-modal transfer. In: C.J.C. Burges, L.\u00a0Bottou, M.\u00a0Welling, Z.\u00a0Ghahramani, K.Q. Weinberger (eds.) Advances in Neural Information Processing Systems 26, pp. 935\u2013943. Curran Associates, Inc. (2013)"},{"key":"2470_CR86","unstructured":"Soomro, K., Zamir, A.R., Shah, M.: UCF101: A dataset of 101 human actions classes from videos in the wild. CoRR abs\/1212.0402 (2012)"},{"key":"2470_CR87","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/s11263-012-0529-4","volume":"100","author":"Y Su","year":"2012","unstructured":"Su, Y., Jurie, F.: Improving image classification using semantic attributes. Int. J. Comput. Vis. 100, 59\u201377 (2012)","journal-title":"Int. J. Comput. Vis."},{"key":"2470_CR88","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-02075-7","author":"X Sun","year":"2020","unstructured":"Sun, X., Gu, J., Sun, H.: Research progress of zero-shot learning. Appl. Intell. (2020). https:\/\/doi.org\/10.1007\/s10489-020-02075-7","journal-title":"Appl. Intell."},{"key":"2470_CR89","first-page":"1453","volume":"6","author":"I Tsochantaridis","year":"2005","unstructured":"Tsochantaridis, I., Joachims, T., Hofmann, T., Altun, Y.: Large margin methods for structured and interdependent output variables. J. Mach. Learn. Res. 6, 1453\u20131484 (2005)","journal-title":"J. Mach. Learn. Res."},{"key":"2470_CR90","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1007\/978-3-319-71246-8_48","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"VK Verma","year":"2017","unstructured":"Verma, V.K., Rai, P.: A simple exponential family framework for zero-shot learning. In: Ceci, M., Hollm\u00e9n, J., Todorovski, L., Vens, C., D\u017eeroski, S. (eds.) Machine Learning and Knowledge Discovery in Databases, pp. 792\u2013808. Springer International Publishing, Cham (2017)"},{"key":"2470_CR91","doi-asserted-by":"publisher","DOI":"10.1145\/3293318","author":"W Wang","year":"2019","unstructured":"Wang, W., Zheng, V.W., Yu, H., Miao, C.: A survey of zero-shot learning: settings, methods, and applications. ACM Trans. Intell. Syst. Technol. (2019). https:\/\/doi.org\/10.1145\/3293318","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"2470_CR92","doi-asserted-by":"publisher","unstructured":"Wang, X., Ji, Q.: A unified probabilistic approach modeling relationships between attributes and objects. In: 2013 IEEE International Conference on Computer Vision, pp. 2120\u20132127 (2013).https:\/\/doi.org\/10.1109\/ICCV.2013.264","DOI":"10.1109\/ICCV.2013.264"},{"key":"2470_CR93","unstructured":"Welinder, P., Branson, S., Mita, T., Wah, C., Schroff, F., Belongie, S., Perona, P.: Caltech-UCSD Birds 200. Tech. Rep. CNS-TR-2010-001, California Institute of Technology (2010)"},{"key":"2470_CR94","doi-asserted-by":"publisher","unstructured":"Xian, Y., Akata, Z., Sharma, G., Nguyen, Q., Hein, M., Schiele, B.: Latent embeddings for zero-shot classification. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 69\u201377 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.15","DOI":"10.1109\/CVPR.2016.15"},{"key":"2470_CR95","doi-asserted-by":"crossref","unstructured":"Xian, Y., Lampert, C.H., Schiele, B., Akata, Z.: Zero-shot learning: a comprehensive evaluation of the good, the bad and the ugly. IEEE Trans. Pattern Anal. Mach. Intell. (2018)","DOI":"10.1109\/CVPR.2017.328"},{"key":"2470_CR96","doi-asserted-by":"publisher","unstructured":"Xian, Y., Lorenz, T., Schiele, B., Akata, Z.: Feature generating networks for zero-shot learning. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5542\u20135551 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00581","DOI":"10.1109\/CVPR.2018.00581"},{"key":"2470_CR97","doi-asserted-by":"crossref","unstructured":"Xian, Y., Schiele, B., Akata, Z.: Zero-shot learning - the good, the bad and the ugly. In: IEEE Computer Vision and Pattern Recognition (CVPR) (2017)","DOI":"10.1109\/CVPR.2017.328"},{"key":"2470_CR98","doi-asserted-by":"publisher","unstructured":"Xie, G.S., Liu, L., Jin, X., Zhu, F., Zhang, Z., Qin, J., Yao, Y., Shao, L.: Attentive region embedding network for zero-shot learning. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9376\u20139385 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00961","DOI":"10.1109\/CVPR.2019.00961"},{"key":"2470_CR99","unstructured":"Xu, W., Xian, Y., Wang, J., Schiele, B., Akata, Z.: Attribute prototype network for zero-shot learning. In: NeurIPS (2020)"},{"key":"2470_CR100","doi-asserted-by":"publisher","unstructured":"Xu, X., Shen, F., Yang, Y., Zhang, D., Shen, H.T., Song, J.: Matrix tri-factorization with manifold regularizations for zero-shot learning. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2007\u20132016 (2017).https:\/\/doi.org\/10.1109\/CVPR.2017.217","DOI":"10.1109\/CVPR.2017.217"},{"key":"2470_CR101","unstructured":"Yang, Y., Teo, C.L., Daum\u00e9, H., Aloimonos, Y.: Corpus-guided sentence generation of natural images. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP \u201911, pp. 444\u2013454. Association for Computational Linguistics, USA (2011)"},{"key":"2470_CR102","doi-asserted-by":"publisher","unstructured":"Yu, F.X., Cao, L., Feris, R.S., Smith, J.R., Chang, S.: Designing category-level attributes for discriminative visual recognition. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp. 771\u2013778 (2013). https:\/\/doi.org\/10.1109\/CVPR.2013.105","DOI":"10.1109\/CVPR.2013.105"},{"key":"2470_CR103","doi-asserted-by":"crossref","unstructured":"Yue, Z., Wang, T., Zhang, H., Sun, Q., Hua, X.S.: Counterfactual zero-shot and open-set visual recognition. In: CVPR (2021)","DOI":"10.1109\/CVPR46437.2021.01515"},{"key":"2470_CR104","doi-asserted-by":"crossref","unstructured":"Zhang, L., Xiang, T., Gong, S.: Learning a deep embedding model for zero-shot learning. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3010\u20133019 (2017)","DOI":"10.1109\/CVPR.2017.321"},{"issue":"1","key":"2470_CR105","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/s13042-010-0001-0","volume":"1","author":"Y Zhang","year":"2010","unstructured":"Zhang, Y., Jin, R., Zhou, Z.H.: Understanding bag-of-words model: a statistical framework. Int. J. Mach. Learn. Cybern. 1(1), 43\u201352 (2010)","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"2470_CR106","doi-asserted-by":"publisher","unstructured":"Zhang, Z., Saligrama, V.: Zero-shot learning via semantic similarity embedding. In: 2015 IEEE International Conference on Computer Vision (ICCV), pp. 4166\u20134174 (2015).https:\/\/doi.org\/10.1109\/ICCV.2015.474","DOI":"10.1109\/ICCV.2015.474"},{"key":"2470_CR107","unstructured":"Zhao, A., Ding, M., Guan, J., Lu, Z., Xiang, T., Wen, J.R.: Domain-invariant projection learning for zero-shot recognition (2018)"},{"key":"2470_CR108","doi-asserted-by":"crossref","unstructured":"Zhao, B., Wu, B., Wu, T., Wang, Y.: Zero-shot learning posed as a missing data problem. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 2616\u20132622 (2017)","DOI":"10.1109\/ICCVW.2017.310"},{"key":"2470_CR109","doi-asserted-by":"publisher","unstructured":"Zhu, Y., Elhoseiny, M., Liu, B., Peng, X., Elgammal, A.: A generative adversarial approach for zero-shot learning from noisy texts. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1004\u20131013 (2018).https:\/\/doi.org\/10.1109\/CVPR.2018.00111","DOI":"10.1109\/CVPR.2018.00111"},{"key":"2470_CR110","volume-title":"Semantic-Guided Multi-Attention Localization for Zero-Shot Learning","author":"Y Zhu","year":"2019","unstructured":"Zhu, Y., Xie, J., Tang, Z., Peng, X., Elgammal, A.: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning. Curran Associates Inc., Red Hook (2019)"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-022-02470-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-022-02470-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-022-02470-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,17]],"date-time":"2023-04-17T08:20:42Z","timestamp":1681719642000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-022-02470-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,30]]},"references-count":110,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["2470"],"URL":"https:\/\/doi.org\/10.1007\/s00371-022-02470-w","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,30]]},"assertion":[{"value":"18 March 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 May 2022","order":2,"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 conflict of interest to disclose. All the authors have participated in writing this paper and the work is original and is not published elsewhere. This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}