{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T07:40:12Z","timestamp":1763106012925},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T00:00:00Z","timestamp":1720742400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T00:00:00Z","timestamp":1720742400000},"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":["SIViP"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s11760-024-03415-7","type":"journal-article","created":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T17:01:36Z","timestamp":1720803696000},"page":"7621-7634","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Image inpainting based on tensor ring decomposition with generative adversarial network"],"prefix":"10.1007","volume":"18","author":[{"given":"Jianjun","family":"Yuan","sequence":"first","affiliation":[]},{"given":"Hong","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Luoming","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Fujun","family":"Wu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,12]]},"reference":[{"doi-asserted-by":"publisher","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), Las Vegas, NV, USA, pp. 770\u2013778 (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.90","key":"3415_CR1","DOI":"10.1109\/CVPR.2016.90"},{"doi-asserted-by":"publisher","unstructured":"Sun, L., Yang, C., Jiang, B.: Dsp-net: Diverse structure prior network for image inpainting. In: 2023 IEEE International Conference on Multimedia and Expo (ICME), Brisbane, Australia, pp. 474\u2013479 (2023). https:\/\/doi.org\/10.1109\/ICME55011.2023.00088","key":"3415_CR2","DOI":"10.1109\/ICME55011.2023.00088"},{"key":"3415_CR3","first-page":"16331","volume":"34","author":"H Ling","year":"2021","unstructured":"Ling, H., Kreis, K., Li, D., Kim, S.W., Torralba, A., Fidler, S.: Editgan: High-precision semantic image editing. Adv. Neural Inf. Process. Syst. 34, 16331\u201316345 (2021)","journal-title":"Adv. Neural Inf. Process. Syst."},{"doi-asserted-by":"publisher","unstructured":"Zhang, T., Huang, H., Feng, C., Cao, L.: Self-supervised bilingual syntactic alignment for neural machine translation. In: AAAI Conference on Artificial Intelligence, vol. 35. Virtual, pp. 14454\u201314462 (2021). https:\/\/doi.org\/10.1609\/aaai.v35i16.17699","key":"3415_CR4","DOI":"10.1609\/aaai.v35i16.17699"},{"doi-asserted-by":"publisher","unstructured":"Xi, A., Bin, F.: Empirical regularization for synthetic sentence pairs in unsupervised neural machine translation. In: AAAI Conference on Artificial Intelligence, vol. 35. Virtual, pp. 12471\u201312479 (2021). https:\/\/doi.org\/10.1609\/aaai.v35i14.17479","key":"3415_CR5","DOI":"10.1609\/aaai.v35i14.17479"},{"doi-asserted-by":"publisher","unstructured":"Hao, H., Wang, Q., Yu, Z., Zhao, Y., Zhang, J., Zong, C.: Synchronous interactive decoding for multilingual neural machine translation. In: AAAI Conference on Artificial Intelligence, vol. 35. Virtual, pp. 12981\u201312988 (2021). https:\/\/doi.org\/10.1609\/aaai.v35i14.17535","key":"3415_CR6","DOI":"10.1609\/aaai.v35i14.17535"},{"doi-asserted-by":"publisher","unstructured":"Hu, Y., Yang, J., Chen, L., Li, K., Sima, C., Zhu, X., Chai, S., Du, S., Lin, T., Wang, W., Lu, L., Jia, X., Liu, Q., Dai, J., Qiao, Y., Li, H.: Planning-oriented autonomous driving. In: 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, pp. 17853\u201317862 (2023). https:\/\/doi.org\/10.1109\/CVPR52729.2023.01712","key":"3415_CR7","DOI":"10.1109\/CVPR52729.2023.01712"},{"doi-asserted-by":"publisher","unstructured":"Wu, B., Wan, A., Yue, X., Keutzer, K.: Squeezeseg: Convolutional neural nets with recurrent crf for real-time road-object segmentation from 3d lidar point cloud. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, pp. 1887\u20131893 (2018). https:\/\/doi.org\/10.1109\/ICRA.2018.8462926","key":"3415_CR8","DOI":"10.1109\/ICRA.2018.8462926"},{"issue":"11","key":"3415_CR9","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y Lecun","year":"1998","unstructured":"Lecun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998). https:\/\/doi.org\/10.1109\/5.726791","journal-title":"Proc. IEEE"},{"doi-asserted-by":"crossref","unstructured":"Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., Huang, T.S.: Generative image inpainting with contextual attention. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, pp. 5505\u20135514 (2018)","key":"3415_CR10","DOI":"10.1109\/CVPR.2018.00577"},{"doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: Medical Image Computing and Computer-Assisted Intervention, pp. 234\u2013241. Springer (2015)","key":"3415_CR11","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"8","key":"3415_CR12","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1109\/83.935036","volume":"10","author":"C Ballester","year":"2001","unstructured":"Ballester, C., Bertalmio, M., Caselles, V., Sapiro, G., Verdera, J.: Filling-in by joint interpolation of vector fields and gray levels. IEEE Trans. Image Process. 10(8), 1200\u20131211 (2001)","journal-title":"IEEE Trans. Image Process."},{"issue":"12","key":"3415_CR13","doi-asserted-by":"publisher","first-page":"3050","DOI":"10.1109\/TIFS.2017.2730822","volume":"12","author":"H Li","year":"2017","unstructured":"Li, H., Luo, W., Huang, J.: Localization of diffusion-based inpainting in digital images. IEEE Trans. Inf. Forensics Secur. 12(12), 3050\u20133064 (2017)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"9","key":"3415_CR14","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1109\/TIP.2004.833105","volume":"13","author":"A Criminisi","year":"2004","unstructured":"Criminisi, A., P\u00e9rez, P., Toyama, K.: Region filling and object removal by exemplar-based image inpainting. IEEE Trans. Image Process. 13(9), 1200\u20131212 (2004)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"3415_CR15","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1145\/1531326.1531330","volume":"28","author":"C Barnes","year":"2009","unstructured":"Barnes, C., Shechtman, E., Finkelstein, A., Goldman, D.B.: Patchmatch: a randomized correspondence algorithm for structural image editing. ACM Trans. Graph. 28(3), 24 (2009)","journal-title":"ACM Trans. Graph."},{"doi-asserted-by":"crossref","unstructured":"Rumelhart, D., Hinton, G., Williams, R.: Learning internal representations by error propagation. ics report 8506. Institute for Cognitive Science, University of California, San Diego 8(1), 2021 (1985)","key":"3415_CR16","DOI":"10.21236\/ADA164453"},{"unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. Advances in neural information processing systems, vol. 27 (2014)","key":"3415_CR17"},{"doi-asserted-by":"crossref","unstructured":"Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., Efros, A.A.: Context encoders: Feature learning by inpainting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA, pp. 2536\u20132544 (2016)","key":"3415_CR18","DOI":"10.1109\/CVPR.2016.278"},{"doi-asserted-by":"crossref","unstructured":"Kim, Y.-D., Park, E., Yoo, S., Choi, T., Yang, L., Shin, D.: Compression of deep convolutional neural networks for fast and low power mobile applications. CoRR arXiv:1511.06530 (2015)","key":"3415_CR19","DOI":"10.14257\/astl.2016.140.36"},{"unstructured":"Novikov, A., Podoprikhin, D., Osokin, A., Vetrov, D.: Tensorizing neural networks. In: Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 1. NIPS\u201915, pp. 442\u2013450. MIT Press, Montr\u00e9al, Canada (2015)","key":"3415_CR20"},{"issue":"3","key":"3415_CR21","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1137\/07070111X","volume":"51","author":"TG Kolda","year":"2009","unstructured":"Kolda, T.G., Bader, B.W.: Tensor decompositions and applications. SIAM Rev. 51(3), 455\u2013500 (2009)","journal-title":"SIAM Rev."},{"issue":"5","key":"3415_CR22","doi-asserted-by":"publisher","first-page":"2295","DOI":"10.1137\/090752286","volume":"33","author":"IV Oseledets","year":"2011","unstructured":"Oseledets, I.V.: Tensor-train decomposition. SIAM J. Sci. Comput. 33(5), 2295\u20132317 (2011)","journal-title":"SIAM J. Sci. Comput."},{"unstructured":"Zhao, Q., Zhou, G., Xie, S., Zhang, L., Cichocki, A.: Tensor ring decomposition. arXiv preprint arXiv:1606.05535 (2016)","key":"3415_CR23"},{"key":"3415_CR24","doi-asserted-by":"publisher","first-page":"2405","DOI":"10.1109\/TIP.2022.3152624","volume":"31","author":"W Quan","year":"2022","unstructured":"Quan, W., Zhang, R., Zhang, Y., Li, Z., Wang, J., Yan, D.-M.: Image inpainting with local and global refinement. IEEE Trans. Image Process. 31, 2405\u20132420 (2022)","journal-title":"IEEE Trans. Image Process."},{"unstructured":"Durugkar, I., Gemp, I., Mahadevan, S.: Generative multi-adversarial networks. arXiv preprint arXiv:1611.01673 (2016)","key":"3415_CR25"},{"key":"3415_CR26","first-page":"29597","volume":"35","author":"J Choi","year":"2022","unstructured":"Choi, J., Han, B.: Mcl-gan: generative adversarial networks with multiple specialized discriminators. Adv. Neural Inf. Process. Syst. 35, 29597\u201329609 (2022)","journal-title":"Adv. Neural Inf. Process. Syst."},{"doi-asserted-by":"crossref","unstructured":"Rojas, D.J.B., Fernandes, B.J.T., Fernandes, S.M.M.: A review on image inpainting techniques and datasets. In: 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Porto de Galinhas, Brazil, pp. 240\u2013247. IEEE (2020)","key":"3415_CR27","DOI":"10.1109\/SIBGRAPI51738.2020.00040"},{"doi-asserted-by":"crossref","unstructured":"Bertalmio, M., Sapiro, G., Caselles, V., Ballester, C.: Image inpainting. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, New Orleans, Louisiana, USA, pp. 417\u2013424 (2000)","key":"3415_CR28","DOI":"10.1145\/344779.344972"},{"doi-asserted-by":"crossref","unstructured":"Cao, C., Fu, Y.: Learning a sketch tensor space for image inpainting of man-made scenes. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, virtual, pp. 14509\u201314518 (2021)","key":"3415_CR29","DOI":"10.1109\/ICCV48922.2021.01424"},{"doi-asserted-by":"crossref","unstructured":"Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., Huang, T.S.: Free-form image inpainting with gated convolution. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, Seoul, South Korea, pp. 4471\u20134480 (2019)","key":"3415_CR30","DOI":"10.1109\/ICCV.2019.00457"},{"doi-asserted-by":"crossref","unstructured":"Guo, Z., Chen, Z., Yu, T., Chen, J., Liu, S.: Progressive image inpainting with full-resolution residual network. In: Proceedings of the 27th ACM International Conference on Multimedia, Nice, France, pp. 2496\u20132504 (2019)","key":"3415_CR31","DOI":"10.1145\/3343031.3351022"},{"doi-asserted-by":"crossref","unstructured":"Cui, Y., Ren, W., Yang, S., Cao, X., Knoll, A.: Irnext: Rethinking convolutional network design for image restoration. In: International Conference on Machine Learning, Honolulu, HI, USA, pp. 6545\u20136564 (2023)","key":"3415_CR32","DOI":"10.1109\/ICCV51070.2023.01195"},{"doi-asserted-by":"crossref","unstructured":"Cui, Y., Tao, Y., Bing, Z., Ren, W., Gao, X., Cao, X., Huang, K., Knoll, A.: Selective frequency network for image restoration. In: The Eleventh International Conference on Learning Representations, Kigali, Rwanda (2023)","key":"3415_CR33","DOI":"10.1109\/ICCV51070.2023.01195"},{"issue":"2","key":"3415_CR34","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1109\/TPAMI.2023.3330416","volume":"46","author":"Y Cui","year":"2024","unstructured":"Cui, Y., Ren, W., Cao, X., Knoll, A.: Image restoration via frequency selection. IEEE Trans. Pattern Anal. Mach. Intell. 46(2), 1093\u20131108 (2024)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"7","key":"3415_CR35","doi-asserted-by":"publisher","first-page":"3266","DOI":"10.1109\/TVCG.2022.3156949","volume":"29","author":"Y Zeng","year":"2023","unstructured":"Zeng, Y., Fu, J., Chao, H., Guo, B.: Aggregated contextual transformations for high-resolution image inpainting. IEEE Trans. Vis. Comput. Graph. 29(7), 3266\u20133280 (2023). https:\/\/doi.org\/10.1109\/TVCG.2022.3156949","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"unstructured":"LeCun, Y., Denker, J., Solla, S.: Optimal brain damage. Advances in neural information processing systems, vol. 2 (1989)","key":"3415_CR36"},{"doi-asserted-by":"crossref","unstructured":"Redfern, A.J., Zhu, L., Newquist, M.K.: Bcnn: A binary cnn with all matrix ops quantized to 1 bit precision. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, virtual, pp. 4604\u20134612 (2021)","key":"3415_CR37","DOI":"10.1109\/CVPRW53098.2021.00518"},{"unstructured":"Hinton, G., Vinyals, O., Dean, J.: Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 (2015)","key":"3415_CR38"},{"doi-asserted-by":"crossref","unstructured":"Chen, Y., Wang, N., Zhang, Z.: Darkrank: Accelerating deep metric learning via cross sample similarities transfer. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32. New Orleans, LA, USA (2018)","key":"3415_CR39","DOI":"10.1609\/aaai.v32i1.11783"},{"issue":"4","key":"3415_CR40","doi-asserted-by":"publisher","first-page":"485","DOI":"10.1109\/JPROC.2020.2976475","volume":"108","author":"L Deng","year":"2020","unstructured":"Deng, L., Li, G., Han, S., Shi, L., Xie, Y.: Model compression and hardware acceleration for neural networks: a comprehensive survey. Proc. IEEE 108(4), 485\u2013532 (2020)","journal-title":"Proc. IEEE"},{"unstructured":"Harshman, R.A., et al.: Foundations of the parafac procedure: models and conditions for an \u201cexplanatory\u201d multimodal factor analysis (1970)","key":"3415_CR41"},{"unstructured":"Hayashi, K., Yamaguchi, T., Sugawara, Y., Maeda, S.: Exploring unexplored tensor network decompositions for convolutional neural networks. Advances in Neural Information Processing Systems, vol. 32 (2019)","key":"3415_CR42"},{"unstructured":"Lebedev, V., Ganin, Y., Rakhuba, M., Oseledets, I., Lempitsky, V.S.: Speeding-up convolutional neural networks using fine-tuned cp-decomposition. CoRR arXiv:1412.6553 (2014)","key":"3415_CR43"},{"key":"3415_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108171","volume":"241","author":"Y Liu","year":"2022","unstructured":"Liu, Y., Ng, M.K.: Deep neural network compression by tucker decomposition with nonlinear response. Knowl. Based Syst. 241, 108171 (2022)","journal-title":"Knowl. Based Syst."},{"doi-asserted-by":"crossref","unstructured":"Chen, Y., Jin, X., Kang, B., Feng, J., Yan, S.: Sharing residual units through collective tensor factorization to improve deep neural networks. In: IJCAI, Stockholm, Sweden, pp. 635\u2013641 (2018)","key":"3415_CR45","DOI":"10.24963\/ijcai.2018\/88"},{"doi-asserted-by":"crossref","unstructured":"Wang, P., Cheng, J.: Accelerating convolutional neural networks for mobile applications. In: Proceedings of the 24th ACM International Conference on Multimedia, Amsterdam, the Netherlands, pp. 541\u2013545 (2016)","key":"3415_CR46","DOI":"10.1145\/2964284.2967280"},{"doi-asserted-by":"crossref","unstructured":"Zhao, Q., Sugiyama, M., Yuan, L., Cichocki, A.: Learning efficient tensor representations with ring-structured networks. In: ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom, pp. 8608\u20138612. IEEE (2019)","key":"3415_CR47","DOI":"10.1109\/ICASSP.2019.8682231"},{"issue":"4","key":"3415_CR48","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1109\/TNANO.2017.2732698","volume":"17","author":"H Huang","year":"2017","unstructured":"Huang, H., Ni, L., Wang, K., Wang, Y., Yu, H.: A highly parallel and energy efficient three-dimensional multilayer cmos-rram accelerator for tensorized neural network. IEEE Trans. Nanotechnol. 17(4), 645\u2013656 (2017)","journal-title":"IEEE Trans. Nanotechnol."},{"unstructured":"Su, J., Li, J., Bhattacharjee, B., Huang, F.: Tensorial neural networks: Generalization of neural networks and application to model compression. arXiv preprint arXiv:1805.10352 (2018)","key":"3415_CR49"},{"doi-asserted-by":"crossref","unstructured":"Mao, X., Li, Q., Xie, H., Lau, R.Y., Wang, Z., Paul\u00a0Smolley, S.: Least squares generative adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, pp. 2794\u20132802 (2017)","key":"3415_CR50","DOI":"10.1109\/ICCV.2017.304"},{"unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: 3rd International Conference on Learning Representations, Conference Track Proceedings, San Diego, CA, USA (2015)","key":"3415_CR51"},{"doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA, pp. 248\u2013255 (2009)","key":"3415_CR52","DOI":"10.1109\/CVPR.2009.5206848"},{"doi-asserted-by":"crossref","unstructured":"Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, the Netherlands, pp. 694\u2013711. Springer (2016)","key":"3415_CR53","DOI":"10.1007\/978-3-319-46475-6_43"},{"doi-asserted-by":"crossref","unstructured":"Gatys, L.A., Ecker, A.S., Bethge, M.: Image style transfer using convolutional neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA, pp. 2414\u20132423 (2016)","key":"3415_CR54","DOI":"10.1109\/CVPR.2016.265"},{"issue":"4","key":"3415_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2185520.2185597","volume":"31","author":"C Doersch","year":"2012","unstructured":"Doersch, C., Singh, S., Gupta, A., Sivic, J., Efros, A.: What makes Paris look like Paris? ACM Trans. Graph. 31(4), 1\u20139 (2012)","journal-title":"ACM Trans. Graph."},{"unstructured":"Karras, T., Aila, T., Laine, S., Lehtinen, J.: Progressive growing of gans for improved quality, stability, and variation. In: 6th International Conference on Learning Representations, Conference Track Proceedings, Vancouver, Canada (2018)","key":"3415_CR56"},{"doi-asserted-by":"crossref","unstructured":"Liu, G., Reda, F.A., Shih, K.J., Wang, T.-C., Tao, A., Catanzaro, B.: Image inpainting for irregular holes using partial convolutions. In: Proceedings of the European Conference on Computer Vision, Munich, Germany, pp. 85\u2013100 (2018)","key":"3415_CR57","DOI":"10.1007\/978-3-030-01252-6_6"},{"doi-asserted-by":"crossref","unstructured":"Li, J., Wang, N., Zhang, L., Du, B., Tao, D.: Recurrent feature reasoning for image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, virtual, pp. 7760\u20137768 (2020)","key":"3415_CR58","DOI":"10.1109\/CVPR42600.2020.00778"},{"doi-asserted-by":"crossref","unstructured":"Deng, Y., Hui, S., Zhou, S., Meng, D., Wang, J.: T-former: An efficient transformer for image inpainting. In: Proceedings of the 30th ACM International Conference on Multimedia, Lisbon, Portugal, pp. 6559\u20136568 (2022)","key":"3415_CR59","DOI":"10.1145\/3503161.3548446"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03415-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-024-03415-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03415-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T17:39:06Z","timestamp":1726249146000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-024-03415-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,12]]},"references-count":59,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["3415"],"URL":"https:\/\/doi.org\/10.1007\/s11760-024-03415-7","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2024,7,12]]},"assertion":[{"value":"26 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 July 2024","order":4,"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 financial interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}