{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T10:50:12Z","timestamp":1744800612604,"version":"3.40.3"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031490170"},{"type":"electronic","value":"9783031490187"}],"license":[{"start":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T00:00:00Z","timestamp":1701043200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T00:00:00Z","timestamp":1701043200000},"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":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-49018-7_1","type":"book-chapter","created":{"date-parts":[[2023,11,26]],"date-time":"2023-11-26T23:02:21Z","timestamp":1701039741000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Deblur Capsule Networks"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5124-3713","authenticated-orcid":false,"given":"Daniel Felipe S.","family":"Santos","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9597-055X","authenticated-orcid":false,"given":"Rafael G.","family":"Pires","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6494-7514","authenticated-orcid":false,"given":"Jo\u00e3o P.","family":"Papa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,27]]},"reference":[{"key":"1_CR1","volume-title":"Digital Image Restoration","author":"HC Andrews","year":"1977","unstructured":"Andrews, H.C., Hunt, B.R.: Digital Image Restoration. Advanced monographs, Prentice-Hall, Prentice-Hall Signal Processing Series (1977)"},{"issue":"2","key":"1_CR2","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1109\/79.581363","volume":"14","author":"MR Banham","year":"1997","unstructured":"Banham, M.R., Katsaggelos, A.K.: Digital image restoration. IEEE Signal Process. Mag. 14(2), 24\u201341 (1997)","journal-title":"IEEE Signal Process. Mag."},{"issue":"5","key":"1_CR3","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1109\/5.53403","volume":"78","author":"J Biemond","year":"1990","unstructured":"Biemond, J., Lagendijk, R.L., Mersereau, R.M.: Iterative methods for image deblurring. Proc. IEEE 78(5), 856\u2013883 (1990)","journal-title":"Proc. IEEE"},{"key":"1_CR4","doi-asserted-by":"crossref","unstructured":"Chen, Z., Zhang, H.: Learning implicit fields for generative shape modeling. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5939\u20135948 (2019)","DOI":"10.1109\/CVPR.2019.00609"},{"issue":"10","key":"1_CR5","doi-asserted-by":"publisher","first-page":"1865","DOI":"10.1109\/JPROC.2017.2675998","volume":"105","author":"G Cheng","year":"2017","unstructured":"Cheng, G., Han, J., Lu, X.: Remote sensing image scene classification: benchmark and state of the art. Proc. IEEE 105(10), 1865\u20131883 (2017)","journal-title":"Proc. IEEE"},{"key":"1_CR6","unstructured":"Gonzalez, R., Woods, R.: Digital Image Processing. Prentice-Hall (2007)"},{"key":"1_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2020.3043627","volume":"60","author":"X Hua","year":"2020","unstructured":"Hua, X., Pan, C., Shi, Y., Liu, J., Hong, H.: Removing atmospheric turbulence effects via geometric distortion and blur representation. IEEE Trans. Geosci. Remote Sens. 60, 1\u201313 (2020)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1_CR8","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"1_CR9","unstructured":"Klambauer, G., Unterthiner, T., Mayr, A., Hochreiter, S.: Self-normalizing neural networks. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 30, pp. 972\u2013981. Curran Associates, Inc. (2017)"},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Levin, A., Weiss, Y., Durand, F., Freeman, W.T.: Understanding and evaluating blind deconvolution algorithms. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1964\u20131971. IEEE Computer Society (2009)","DOI":"10.1109\/CVPR.2009.5206815"},{"key":"1_CR11","first-page":"1","volume":"60","author":"H Liu","year":"2022","unstructured":"Liu, H., Gu, Y.: Deep joint estimation network for satellite video super-resolution with multiple degradations. IEEE Trans. Geosci. Remote Sens. 60, 1\u201315 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1_CR12","doi-asserted-by":"crossref","unstructured":"Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: Proceedings of the 8th International Conference on Computer Vision, vol. 2, pp. 416\u2013423 (2001)","DOI":"10.1109\/ICCV.2001.937655"},{"issue":"3","key":"1_CR13","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","volume":"20","author":"A Mittal","year":"2012","unstructured":"Mittal, A., Soundararajan, R., Bovik, A.C.: Making a \u201ccompletely blind\u2019\u2019 image quality analyzer. IEEE Signal Process. Lett. 20(3), 209\u2013212 (2012)","journal-title":"IEEE Signal Process. Lett."},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Nah, S., Hyun Kim, T., Mu Lee, K.: Deep multi-scale convolutional neural network for dynamic scene deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3883\u20133891 (2017)","DOI":"10.1109\/CVPR.2017.35"},{"key":"1_CR15","doi-asserted-by":"crossref","unstructured":"Ren, D., Zhang, K., Wang, Q., Hu, Q., Zuo, W.: Neural blind deconvolution using deep priors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3341\u20133350 (2020)","DOI":"10.1109\/CVPR42600.2020.00340"},{"key":"1_CR16","unstructured":"Sabour, S., Frosst, N., Hinton, G.E.: Dynamic routing between capsules. In: Guyon, I., et al. (eds.) Advances in Neural Information Processing Systems, vol. 30, pp. 3859\u20133869. Curran Associates, Inc. (2017)"},{"issue":"2","key":"1_CR17","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1109\/LGRS.2018.2870732","volume":"16","author":"I Sacramento","year":"2018","unstructured":"Sacramento, I., Trindade, E., Roisenberg, M., Bordignon, F., Rodrigues, B.B.: Acoustic impedance deblurring with a deep convolution neural network. IEEE Geosci. Remote Sens. Lett. 16(2), 315\u2013319 (2018)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"1_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2022.3166352","volume":"60","author":"Q Safder","year":"2022","unstructured":"Safder, Q., et al.: Ba_EnCaps: dense capsule architecture for thermal scrutiny. IEEE Trans. Geosci. Remote Sens. 60, 1\u201311 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"7","key":"1_CR19","doi-asserted-by":"publisher","first-page":"1439","DOI":"10.1109\/TPAMI.2015.2481418","volume":"38","author":"CJ Schuler","year":"2015","unstructured":"Schuler, C.J., Hirsch, M., Harmeling, S., Sch\u00f6lkopf, B.: Learning to deblur. IEEE Trans. Pattern Anal. Mach. Intell. 38(7), 1439\u20131451 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"1_CR20","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/LGRS.2012.2190038","volume":"9","author":"H Shen","year":"2012","unstructured":"Shen, H., Du, L., Zhang, L., Gong, W.: A blind restoration method for remote sensing images. IEEE Geosci. Remote Sens. Lett. 9(6), 1137\u20131141 (2012)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"1_CR21","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Tao, X., Gao, H., Shen, X., Wang, J., Jia, J.: Scale-recurrent network for deep image deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8174\u20138182 (2018)","DOI":"10.1109\/CVPR.2018.00853"},{"key":"1_CR23","doi-asserted-by":"crossref","unstructured":"Ulyanov, D., Vedaldi, A., Lempitsky, V.: Deep image prior. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9446\u20139454 (2018)","DOI":"10.1109\/CVPR.2018.00984"},{"key":"1_CR24","doi-asserted-by":"crossref","unstructured":"Vasu, S., Maligireddy, V.R., Rajagopalan, A.: Non-blind deblurring: handling kernel uncertainty with CNNs. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3272\u20133281 (2018)","DOI":"10.1109\/CVPR.2018.00345"},{"issue":"9","key":"1_CR25","doi-asserted-by":"publisher","first-page":"6633","DOI":"10.1109\/TGRS.2019.2907567","volume":"57","author":"X Wang","year":"2019","unstructured":"Wang, X., Zhong, Y., Zhang, L., Xu, Y.: Blind hyperspectral unmixing considering the adjacency effect. IEEE Trans. Geosci. Remote Sens. 57(9), 6633\u20136649 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"8","key":"1_CR26","doi-asserted-by":"publisher","first-page":"2923","DOI":"10.1109\/TCSVT.2020.3034137","volume":"31","author":"F Wen","year":"2021","unstructured":"Wen, F., Ying, R., Liu, Y., Liu, P., Truong, T.K.: A simple local minimal intensity prior and an improved algorithm for blind image deblurring. IEEE Trans. Circuits Syst. Video Technol. 31(8), 2923\u20132937 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"2","key":"1_CR27","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1109\/TASSP.1981.1163533","volume":"29","author":"J Woods","year":"1981","unstructured":"Woods, J., Ingle, V.: Kalman filtering in two dimensions: further results. IEEE Trans. Acoust. Speech Signal Process. 29(2), 188\u2013197 (1981)","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"issue":"7","key":"1_CR28","doi-asserted-by":"publisher","first-page":"3965","DOI":"10.1109\/TGRS.2017.2685945","volume":"55","author":"GS Xia","year":"2017","unstructured":"Xia, G.S., et al.: AID: a benchmark data set for performance evaluation of aerial scene classification. IEEE Trans. Geosci. Remote Sens. 55(7), 3965\u20133981 (2017)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"1_CR29","first-page":"1910","volume":"25","author":"R Yan","year":"2016","unstructured":"Yan, R., Shao, L.: Blind image blur estimation via deep learning. IEEE Trans. Image Process. 25(4), 1910\u20131921 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"1_CR30","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., et al.: Multi-stage progressive image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14821\u201314831 (2021)","DOI":"10.1109\/CVPR46437.2021.01458"},{"issue":"7","key":"1_CR31","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","volume":"26","author":"K Zhang","year":"2017","unstructured":"Zhang, K., Zuo, W., Chen, Y., Meng, D., Zhang, L.: Beyond a gaussian denoiser: residual learning of deep CNN for image denoising. IEEE Trans. Image Process. 26(7), 3142\u20133155 (2017)","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"1_CR32","doi-asserted-by":"publisher","first-page":"494","DOI":"10.3390\/rs11050494","volume":"11","author":"W Zhang","year":"2019","unstructured":"Zhang, W., Tang, P., Zhao, L.: Remote sensing image scene classification using CNN-CapsNet. Remote Sens. 11(5), 494 (2019)","journal-title":"Remote Sens."}],"container-title":["Lecture Notes in Computer Science","Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-49018-7_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T10:58:00Z","timestamp":1730631480000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-49018-7_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,27]]},"ISBN":["9783031490170","9783031490187"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-49018-7_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023,11,27]]},"assertion":[{"value":"27 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CIARP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Iberoamerican Congress on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Coimbra","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ciarp2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conftool","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"106","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"61","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"58% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}