{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T06:33:14Z","timestamp":1784010794184,"version":"3.55.0"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"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":["Int J Comput Vis"],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s11263-025-02504-5","type":"journal-article","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T10:49:22Z","timestamp":1751539762000},"page":"6896-6911","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Semantic Masking with Curriculum Learning for Robust HDR Image Reconstruction"],"prefix":"10.1007","volume":"133","author":[{"given":"Zhangkai","family":"Ni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kerui","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenhan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanli","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sam","family":"Kwong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,3]]},"reference":[{"key":"2504_CR1","unstructured":"Alec, R., Karthik, N., Tim, S., Ilya, S., and others. (2018). Improving language understanding by generative pre-training."},{"key":"2504_CR2","doi-asserted-by":"crossref","unstructured":"Ankner, Z., Saphra, N., Blalock, D., Frankle, J., & Leavitt, M.\u00a0L. (2023.) Dynamic masking rate schedules for mlm pretraining. arXiv preprint arXiv:2305.15096.","DOI":"10.18653\/v1\/2024.eacl-short.42"},{"key":"2504_CR3","unstructured":"Bao, H., Dong, L., Piao, S., & Wei, F. (2021). BEiT: BERT pre-training of image transformers. In International Conference on Learning Representations."},{"key":"2504_CR4","first-page":"7","volume":"3","author":"L Bogoni","year":"2000","unstructured":"Bogoni, L. (2000). Extending dynamic range of monochrome and color images through fusion. In IEEE International Conference on Pattern Recognition, 3, 7\u201312.","journal-title":"In IEEE International Conference on Pattern Recognition"},{"key":"2504_CR5","doi-asserted-by":"crossref","unstructured":"Chen, H., Gu, J., Liu, Y., Magid, S\u00a0A., Dong, C., Wang, Q., Pfister, H., & Zhu, L. (2023). Masked image training for generalizable deep image denoising. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1692\u20131703.","DOI":"10.1109\/CVPR52729.2023.00169"},{"key":"2504_CR6","doi-asserted-by":"crossref","unstructured":"Chen, X., Li, H., Li, M., & Pan, J. (2023). Learning a sparse transformer network for effective image deraining. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5896\u20135905.","DOI":"10.1109\/CVPR52729.2023.00571"},{"key":"2504_CR7","doi-asserted-by":"crossref","unstructured":"Chen, R., Zheng, B., Zhang, H., Chen, Q., Yan, C., Slabaugh, G., & Yuan, S. (2023). Improving dynamic HDR imaging with fusion transformer. In Proceedings of the AAAI Conference on Artificial Intelligence, 340\u2013349.","DOI":"10.1609\/aaai.v37i1.25107"},{"key":"2504_CR8","doi-asserted-by":"crossref","unstructured":"Debevec, P.\u00a0E, & Malik, J. (1997). Recovering high dynamic range radiance maps from photographs. In Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques, 369\u2013378.","DOI":"10.1145\/258734.258884"},{"key":"2504_CR9","unstructured":"Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of NAACL-HLT, 4171\u20134186."},{"key":"2504_CR10","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., & Houlsby, N. (2021). An image is worth 16x16 words: Transformers for image recognition at scale. In International Conference on Learning Representations."},{"issue":"6","key":"2504_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3130800.3130816","volume":"36","author":"G Eilertsen","year":"2017","unstructured":"Eilertsen, G., Kronander, J., Denes, G., Mantiuk, R. K., & Unger, J. (2017). Hdr image reconstruction from a single exposure using deep cnns. ACM Transactions on Graphics, 36(6), 1\u201315.","journal-title":"ACM Transactions on Graphics"},{"issue":"3","key":"2504_CR12","first-page":"2","volume":"277284","author":"T Grosch","year":"2006","unstructured":"Grosch, T., et al. (2006). Fast and robust high dynamic range image generation with camera and object movement. Vision, Modeling and Visualization, RWTH Aachen, 277284(3), 2.","journal-title":"Vision, Modeling and Visualization, RWTH Aachen"},{"key":"2504_CR13","doi-asserted-by":"crossref","unstructured":"He, K., Chen, X., Xie, S., Li, Y., Doll\u00e1r, P., & Girshick, R. (2022). Masked autoencoders are scalable vision learners. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 16000\u201316009.","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"2504_CR14","doi-asserted-by":"crossref","unstructured":"Hu, J., Gallo, O., Pulli, K., & Sun, X. (2013) HDR deghosting: How to deal with saturation? In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1163\u20131170.","DOI":"10.1109\/CVPR.2013.154"},{"key":"2504_CR15","doi-asserted-by":"crossref","unstructured":"Hu, T., Yan, Q., Qi, Y., & Zhang, Y. (2024). Generating content for hdr deghosting from frequency view. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 25732\u201325741.","DOI":"10.1109\/CVPR52733.2024.02431"},{"issue":"4","key":"2504_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3072959.3073609","volume":"36","author":"NK Kalantari","year":"2017","unstructured":"Kalantari, N. K., & Ramamoorthi, R. (2017). Deep high dynamic range imaging of dynamic scenes. ACM Transactions on Graphics, 36(4), 1\u201312.","journal-title":"ACM Transactions on Graphics"},{"issue":"3","key":"2504_CR17","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1145\/882262.882270","volume":"22","author":"SB Kang","year":"2003","unstructured":"Kang, S. B., Uyttendaele, M., Winder, S., & Szeliski, R. (2003). High dynamic range video. ACM Transactions on Graphics, 22(3), 319\u2013325.","journal-title":"ACM Transactions on Graphics"},{"key":"2504_CR18","doi-asserted-by":"crossref","unstructured":"Kong, L., Li, B., Xiong, Y., Zhang, H., Gu, H., & Chen, J. (2024). SAFNet: Selective alignment fusion network for efficient hdr imaging. In Proceedings of the European Conference on Computer Vision.","DOI":"10.1007\/978-3-031-73347-5_15"},{"key":"2504_CR19","doi-asserted-by":"crossref","unstructured":"Le, P.-H., Le, Q., Nguyen, R., & Hua, B.-S. (2023). Single-image hdr reconstruction by multi-exposure generation. In Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, 4063\u20134072.","DOI":"10.1109\/WACV56688.2023.00405"},{"key":"2504_CR20","unstructured":"Li, X., Wang, W., Yang, L., & Yang, J. (2022). Uniform masking: Enabling mae pre-training for pyramid-based vision transformers with locality. arXiv preprint arXiv:2205.10063."},{"key":"2504_CR21","doi-asserted-by":"crossref","unstructured":"Liang, J., Cao, J., Sun, G., Zhang, K., Van\u00a0Gool, L., & Timofte, R. (2021). SwinIR: Image restoration using swin transformer. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1833\u20131844.","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"2504_CR22","doi-asserted-by":"crossref","unstructured":"Liu, Y.-L., Lai, W.-S., Chen, Y.-S., Kao, Y.-L., Yang, M.-H., Chuang, Y.-Y., & Huang, J.-B.. (2020). Single-image HDR reconstruction by learning to reverse the camera pipeline. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1651\u20131660.","DOI":"10.1109\/CVPR42600.2020.00172"},{"key":"2504_CR23","doi-asserted-by":"crossref","unstructured":"Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., & Guo, B. (2021) Swin Transformer: Hierarchical vision transformer using shifted windows. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, 10012\u201310022.","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"2504_CR24","doi-asserted-by":"crossref","unstructured":"Liu, Z., Wang, Y., Zeng, B., & Liu, S., (2022). Ghost-free high dynamic range imaging with context-aware transformer. In Proceedings of the European Conference on Computer Vision, 344\u2013360.","DOI":"10.1007\/978-3-031-19800-7_20"},{"key":"2504_CR25","doi-asserted-by":"crossref","unstructured":"Liu, S., Zhang, X., Sun, L., Liang, Z., Zeng, H., & Zhang, L. (2023). Joint hdr denoising and fusion: A real-world mobile hdr image dataset. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 13966\u201313975.","DOI":"10.1109\/CVPR52729.2023.01342"},{"key":"2504_CR26","first-page":"14290","volume":"35","author":"G Li","year":"2022","unstructured":"Li, G., Zheng, H., Liu, D., Wang, C., Bing, S., & Zheng, C. (2022). Semmae: Semantic-guided masking for learning masked autoencoders. Advances in Neural Information Processing Systems, 35, 14290\u201314302.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"2504_CR27","doi-asserted-by":"crossref","unstructured":"Madan, N., Ristea, N.-C., Nasrollahi, K., Moeslund, T.\u00a0B., & Ionescu, R.\u00a0T. (2024). Cl-mae: Curriculum-learned masked autoencoders. In Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, 2492\u20132502.","DOI":"10.1109\/WACV57701.2024.00248"},{"issue":"5","key":"2504_CR28","doi-asserted-by":"publisher","first-page":"2519","DOI":"10.1109\/TIP.2017.2671921","volume":"26","author":"K Ma","year":"2017","unstructured":"Ma, K., Li, H., Yong, H., Wang, Z., Meng, D., & Zhang, L. (2017). Robust multi-exposure image fusion: a structural patch decomposition approach. IEEE Transactions on Image Processing, 26(5), 2519\u20132532.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"4","key":"2504_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2010324.1964935","volume":"30","author":"R Mantiuk","year":"2011","unstructured":"Mantiuk, R., Kim, K. J., Rempel, A. G., & Heidrich, W. (2011). Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions. ACM Transactions on Graphics, 30(4), 1\u201314.","journal-title":"ACM Transactions on Graphics"},{"key":"2504_CR30","doi-asserted-by":"crossref","unstructured":"Ni, Z., Yang, W., Wang, H., Wang, S., Ma, L., & Kwong, S. (2022). Cycle-interactive generative adversarial network for robust unsupervised low-light enhancement. In Proceedings of the 30th ACM International Conference on Multimedia, 1484\u20131492.","DOI":"10.1145\/3503161.3548006"},{"key":"2504_CR31","doi-asserted-by":"publisher","first-page":"3885","DOI":"10.1109\/TIP.2021.3064433","volume":"30","author":"Y Niu","year":"2021","unstructured":"Niu, Y., Jianbin, W., Liu, W., Guo, W., & Lau, R. W. H. (2021). HDR-GAN: HDR image reconstruction from multi-exposed ldr images with large motions. IEEE Transactions on Image Processing, 30, 3885\u20133896.","journal-title":"IEEE Transactions on Image Processing"},{"key":"2504_CR32","unstructured":"Prabhakar, K.\u00a0R., & Babu, R.\u00a0V.. (2020). High dynamic range deghosting dataset. Data retrieved from IISc VAL website https:\/\/val.cds.iisc.ac.in\/HDR\/HDRD\/."},{"key":"2504_CR33","doi-asserted-by":"crossref","unstructured":"Prabhakar, K.\u00a0R., Arora, R., Swaminathan, A., Singh, K.\u00a0P., & Babu, R.\u00a0V. (2019). A fast, scalable, and reliable deghosting method for extreme exposure fusion. In IEEE International Conference on Computational Photography, 1\u20138.","DOI":"10.1109\/ICCPHOT.2019.8747329"},{"issue":"8","key":"2504_CR34","first-page":"9","volume":"1","author":"A Radford","year":"2019","unstructured":"Radford, A., Jeffrey, W., Child, R., Luan, D., Amodei, D., Sutskever, I., et al. (2019). Language models are unsupervised multitask learners. OpenAI blog, 1(8), 9.","journal-title":"OpenAI blog"},{"key":"2504_CR35","doi-asserted-by":"crossref","unstructured":"Sehwag, V., Kong, X., Li, J., Spranger, M., & Lyu, L. (2024). Stretching each dollar: Diffusion training from scratch on a micro-budget. arXiv preprint arXiv:2407.15811.","DOI":"10.1109\/CVPR52734.2025.02663"},{"issue":"6","key":"2504_CR36","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1145\/2366145.2366222","volume":"31","author":"P Sen","year":"2012","unstructured":"Sen, P., Kalantari, N. K., Yaesoubi, M., Darabi, S., Goldman, D. B., & Shechtman, E. (2012). Robust patch-based hdr reconstruction of dynamic scenes. ACM Transactions on Graphics, 31(6), 203.","journal-title":"ACM Transactions on Graphics"},{"key":"2504_CR37","unstructured":"Simonyan, K., & Zisserman, A. (2015). Very deep convolutional networks for large-scale image recognition. In International Conference on Learning Representations."},{"issue":"6","key":"2504_CR38","first-page":"1219","volume":"37","author":"O Tae-Hyun","year":"2014","unstructured":"Tae-Hyun, O., Lee, J.-Y., Tai, Y.-W., & Kweon, I. S. (2014). Robust high dynamic range imaging by rank minimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(6), 1219\u20131232.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"2504_CR39","doi-asserted-by":"crossref","unstructured":"Tel, S., Wu, Z., Zhang, Y., Heyrman, B., Demonceaux, C., Timofte, R., & Ginhac, D. (2023). Alignment-free hdr deghosting with semantics consistent transformer. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, pages 12836\u201312845.","DOI":"10.1109\/ICCV51070.2023.01179"},{"key":"2504_CR40","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., & Kweon, I.\u00a0S. (2018). Cbam: Convolutional block attention module. In Proceedings of the European Conference on Computer Vision, 3\u201319.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"2504_CR41","doi-asserted-by":"crossref","unstructured":"Wu, S., Jiarui, X., Yu-Wing, T., & Chi-Keung, T. (2018). Deep high dynamic range imaging with large foreground motions. In Proceedings of the European Conference on Computer Vision, 117\u2013132.","DOI":"10.1007\/978-3-030-01216-8_8"},{"key":"2504_CR42","doi-asserted-by":"crossref","unstructured":"Yan, Q., Chen, W., Zhang, S., Zhu, Y., Sun, J., & Zhang, Y. (2023). A unified HDR imaging method with pixel and patch level. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 22211\u201322220.","DOI":"10.1109\/CVPR52729.2023.02127"},{"key":"2504_CR43","doi-asserted-by":"crossref","unstructured":"Yan, Q., Gong, D., Shi, Q., van\u00a0den Hengel, A., Shen, C., Reid, I., & Zhang, Y. (2019). Attention-guided network for ghost-free high dynamic range imaging. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 1751\u20131760.","DOI":"10.1109\/CVPR.2019.00185"},{"key":"2504_CR44","doi-asserted-by":"crossref","unstructured":"Yan, Q., Gong, D., Zhang, P., Shi, Q., Sun, J., Reid, I., & Zhang, Y. (2019). Multi-scale dense networks for deep high dynamic range imaging. In 2019 IEEE Winter Conference on Applications of Computer Vision, 41\u201350. IEEE.","DOI":"10.1109\/WACV.2019.00012"},{"key":"2504_CR45","doi-asserted-by":"crossref","unstructured":"Yan, Q., Hu, T., Sun, Y., Tang, H., Zhu, Y., Dong, W., Van\u00a0Gool, L., & Zhang, Y. (2023). Towards high-quality hdr deghosting with conditional diffusion models. IEEE Transactions on Circuits and Systems for Video Technology.","DOI":"10.1109\/TCSVT.2023.3326293"},{"key":"2504_CR46","doi-asserted-by":"crossref","unstructured":"Yan, Q., Yang, K., Hu, T., Chen, G., Dai, K., Wu, P., Ren, W., & Zhang, Y. (2024). From dynamic to static: Stepwisely generate hdr image for ghost removal. IEEE Transactions on Circuits and Systems for Video Technology.","DOI":"10.1109\/TCSVT.2024.3467259"},{"key":"2504_CR47","doi-asserted-by":"crossref","unstructured":"Yan, Q., Zhang, S., Chen, W., Tang, H., Zhu, Y., Sun, J., Van\u00a0Gool, L., & Zhang, Y. (2023). SMAE: Few-shot learning for hdr deghosting with saturation-aware masked autoencoders. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5775\u20135784.","DOI":"10.1109\/CVPR52729.2023.00559"},{"key":"2504_CR48","unstructured":"Yang, D., Zhang, Z., & Zhao, H. (2022). Learning better masking for better language model pre-training. arXiv preprintarXiv:2208.10806."},{"key":"2504_CR49","doi-asserted-by":"publisher","first-page":"4308","DOI":"10.1109\/TIP.2020.2971346","volume":"29","author":"Q Yan","year":"2020","unstructured":"Yan, Q., Lei Zhang, Yu., Zhu, L. Y., Sun, J., Shi, Q., & Zhang, Y. (2020). Deep HDR imaging via a non-local network. IEEE Transactions on Image Processing, 29, 4308\u20134322.","journal-title":"IEEE Transactions on Image Processing"},{"key":"2504_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.110802","volume":"156","author":"Q Yan","year":"2024","unstructured":"Yan, Q., Wang, H., Ma, Y., Liu, Y., Dong, W., Wo\u017aniak, M., & Zhang, Y. (2024). Uncertainty estimation in hdr imaging with bayesian neural networks. Pattern Recognition, 156, Article 110802.","journal-title":"Pattern Recognition"},{"key":"2504_CR51","doi-asserted-by":"crossref","unstructured":"Zamir, S.\u00a0W., Arora, A., Khan, S., Hayat, M., Khan, F.\u00a0S., & Yang, M.-H. (2022). Restormer: Efficient transformer for high-resolution image restoration. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5728\u20135739.","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"2504_CR52","doi-asserted-by":"crossref","unstructured":"Zhang, W., & Cham, W.-K. (2011). Gradient-directed multiexposure composition. IEEE Transactions on Image Processing, 21(4), 2318\u20132323.","DOI":"10.1109\/TIP.2011.2170079"},{"issue":"4","key":"2504_CR53","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1016\/j.inffus.2012.05.002","volume":"14","author":"Y Zhang","year":"2013","unstructured":"Zhang, Y., Zhang, H., Nasrabadi, N. M., & Huang, T. S. (2013). Multi-metric learning for multi-sensor fusion based classification. Information Fusion, 14(4), 431\u2013440.","journal-title":"Information Fusion"},{"key":"2504_CR54","unstructured":"Zheng, H., Nie, W., Vahdat, A., & Anandkumar, A. (2023). Fast training of diffusion models with masked transformers. arXiv preprint arXiv:2306.09305."},{"key":"2504_CR55","doi-asserted-by":"crossref","unstructured":"Zhu, L., Zhou, F., Liu, B., & Goksel, O. (2024). Hdrfeat: A feature-rich network for high dynamic range image reconstruction. Pattern Recognition Letters.","DOI":"10.1016\/j.patrec.2024.06.019"},{"key":"2504_CR56","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1111\/j.1467-8659.2011.01870.x","volume":"30","author":"H Zimmer","year":"2011","unstructured":"Zimmer, H., Bruhn, A., & Weickert, J. (2011). Freehand HDR imaging of moving scenes with simultaneous resolution enhancement. In Computer Graphics Forum, 30, 405\u2013414.","journal-title":"In Computer Graphics Forum"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-025-02504-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-025-02504-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-025-02504-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T08:48:59Z","timestamp":1760086139000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-025-02504-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,3]]},"references-count":56,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["2504"],"URL":"https:\/\/doi.org\/10.1007\/s11263-025-02504-5","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,3]]},"assertion":[{"value":"16 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 June 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 July 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}