{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T23:03:47Z","timestamp":1784070227880,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":14,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819237180","type":"print"},{"value":"9789819237197","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3719-7_6","type":"book-chapter","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T22:06:11Z","timestamp":1784066771000},"page":"66-78","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["IPKDUN: An Interpretable Deep Unfolding Network with Implicit Neural Representation and Multi-scale Interaction"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-6165-5719","authenticated-orcid":false,"given":"Jinjie","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6784-3999","authenticated-orcid":false,"given":"Yuli","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9880-0749","authenticated-orcid":false,"given":"Ziheng","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9271-1068","authenticated-orcid":false,"given":"Zixuan","family":"Pei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-6391-491X","authenticated-orcid":false,"given":"Xin","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,15]]},"reference":[{"issue":"3","key":"6_CR1","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1097\/PAP.0b013e318253459e","volume":"19","author":"TC Cornish","year":"2012","unstructured":"Cornish, T.C., Swapp, R.E., Kaplan, K.J.: Whole-slide imaging: routine pathologic diagnosis. Adv. Anat. Pathol. 19(3), 152\u2013159 (2012)","journal-title":"Adv. Anat. Pathol."},{"issue":"2","key":"6_CR2","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/TPAMI.2015.2439281","volume":"38","author":"C Dong","year":"2016","unstructured":"Dong, C., Loy, C.C., He, K., et al.: Image super-resolution using deep convolutional networks. IEEE Trans. Pattern Anal. Mach. Intell. 38(2), 295\u2013307 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"6_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1007\/978-3-319-46475-6_25","volume-title":"Computer Vision \u2013 ECCV 2016","author":"C Dong","year":"2016","unstructured":"Dong, C., Loy, C.C., Tang, X.: Accelerating the super-resolution convolutional neural network. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9906, pp. 391\u2013407. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46475-6_25"},{"key":"6_CR4","doi-asserted-by":"crossref","unstructured":"Shi, W., Caballero, J., Husz\u00e1r, F.: Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1874\u20131883. IEEE (2016)","DOI":"10.1109\/CVPR.2016.207"},{"key":"6_CR5","doi-asserted-by":"crossref","unstructured":"Kim, J., Lee, J.K., Lee, K.M..: Accurate image super-resolution using very deep convolutional networks. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1646\u20131654. IEEE (2016)","DOI":"10.1109\/CVPR.2016.182"},{"key":"6_CR6","doi-asserted-by":"crossref","unstructured":"Lim, B., Son, S., Kim, H.: Enhanced deep residual networks for single image super-resolution. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1132\u20131140. IEEE (2017)","DOI":"10.1109\/CVPRW.2017.151"},{"key":"6_CR7","doi-asserted-by":"crossref","unstructured":"Ledig, C., Theis, L., Husz\u00e1r, F.: Photo-realistic single image super-resolution using a generative adversarial network. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 105\u2013114. IEEE (2017)","DOI":"10.1109\/CVPR.2017.19"},{"key":"6_CR8","doi-asserted-by":"crossref","unstructured":"Tong, T., Li, G., Liu, X., et al.: Image super-resolution using dense skip connections. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 4809\u20134817. IEEE (2017)","DOI":"10.1109\/ICCV.2017.514"},{"key":"6_CR9","doi-asserted-by":"crossref","unstructured":"Liu, Z., Lin, Y., Cao, Y.: Swin transformer: hierarchical vision transformer using shifted windows. In: 2021 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 9992\u201310002. IEEE, Montreal, QC, Canada (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"6_CR10","doi-asserted-by":"crossref","unstructured":"Chen, H., Wang, Y., Guo, T.: Pre-trained image processing transformer. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12294\u201312305. IEEE, Nashville, TN, USA (2021)","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Chen, Y., Liu, S., Wang, X.: Learning continuous image representation with local implicit image function. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8624\u20138634. IEEE, Nashville, TN, USA (2021)","DOI":"10.1109\/CVPR46437.2021.00852"},{"key":"6_CR12","doi-asserted-by":"crossref","unstructured":"Lee, J., Jin, K.H.: Local texture estimator for implicit representation function. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1919\u20131928. IEEE, New Orleans, LA, USA (2022)","DOI":"10.1109\/CVPR52688.2022.00197"},{"key":"6_CR13","doi-asserted-by":"crossref","unstructured":"Cai, X., Lai, Q., Wang, Y.: Poly kernel inception network for remote sensing detection. In: 2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 27706\u201327716. IEEE, Seattle, WA, USA (2024)","DOI":"10.1109\/CVPR52733.2024.02617"},{"issue":"2","key":"6_CR14","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1007\/s41095-022-0277-5","volume":"9","author":"J Xu","year":"2023","unstructured":"Xu, J., Yuan, M., Yan, D.M., et al.: Deep unfolding multi-scale regularizer network for image denoising. Comput. Vis. Media 9(2), 335\u2013350 (2023)","journal-title":"Comput. Vis. Media"}],"container-title":["Lecture Notes in Computer Science","Bioinformatics Research and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3719-7_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T22:06:12Z","timestamp":1784066772000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3719-7_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,15]]},"ISBN":["9789819237180","9789819237197"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3719-7_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,15]]},"assertion":[{"value":"15 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests.","order":1,"name":"Ethics","label":"Disclosure of Interests","group":{"name":"EthicsHeading","label":"Ethics"}},{"value":"ISBRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Bioinformatics Research and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Macao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isbra2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}