{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T16:48:06Z","timestamp":1765039686135,"version":"3.37.3"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020AAA0109602"],"award-info":[{"award-number":["2020AAA0109602"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015401","name":"Key Research and Development Program of Shaanxi Province","doi-asserted-by":"publisher","award":["2021GY-025","2021GXLH-Z-097"],"award-info":[{"award-number":["2021GY-025","2021GXLH-Z-097"]}],"id":[{"id":"10.13039\/501100015401","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council (ARC) Linkage Programs","doi-asserted-by":"publisher","award":["LP220100390","LP220100389"],"award-info":[{"award-number":["LP220100390","LP220100389"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Discovery Program","award":["DP210101347"],"award-info":[{"award-number":["DP210101347"]}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tip.2023.3246792","type":"journal-article","created":{"date-parts":[[2023,2,28]],"date-time":"2023-02-28T18:55:59Z","timestamp":1677610559000},"page":"1583-1598","source":"Crossref","is-referenced-by-count":23,"title":["Dynamic Slimmable Denoising Network"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6787-5499","authenticated-orcid":false,"given":"Zutao","family":"Jiang","sequence":"first","affiliation":[{"name":"School of Software Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8486-7482","authenticated-orcid":false,"given":"Changlin","family":"Li","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7778-8807","authenticated-orcid":false,"given":"Xiaojun","family":"Chang","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6468-5729","authenticated-orcid":false,"given":"Ling","family":"Chen","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3081-8781","authenticated-orcid":false,"given":"Jihua","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0512-880X","authenticated-orcid":false,"given":"Yi","family":"Yang","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia"}]}],"member":"263","reference":[{"key":"ref1","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref3","first-page":"6105","article-title":"Efficientnet: Rethinking model scaling for convolutional neural networks","volume-title":"Proc. ICML","author":"Tan"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.24963\/ijcai.2018\/309"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/ICCV.2017.155"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/ICCV.2019.00339"},{"key":"ref7","first-page":"1","article-title":"Distilling the knowledge in a neural network","volume-title":"Proc. NeurIPS Workshop","author":"Hinton"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1109\/CVPR.2018.00286"},{"key":"ref9","first-page":"1","article-title":"Channel gating neural networks","volume-title":"Proc. NeurIPS","volume":"32","author":"Hua"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1007\/978-3-030-01246-5_1"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1007\/978-3-030-01261-8_25"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1109\/CVPR46437.2021.00850"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1109\/ICCV.2019.00260"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1609\/aaai.v35i4.16412"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/TMM.2016.2602938"},{"key":"ref16","article-title":"Dynamic neural networks: A survey","author":"Han","year":"2021","journal-title":"arXiv:2102.04906"},{"key":"ref17","first-page":"1","article-title":"Multi-scale dense networks for resource efficient image classification","volume-title":"Proc. ICLR","author":"Huang"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1007\/978-3-030-58536-5_11"},{"key":"ref19","first-page":"6166","article-title":"Adaptive neural trees","volume-title":"Proc. ICML","author":"Tanno"},{"key":"ref20","first-page":"1","article-title":"Slimmable neural networks","volume-title":"Proc. ICLR","author":"Yu"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1109\/ICCV.2019.00189"},{"key":"ref22","first-page":"1","article-title":"Natural image denoising with convolutional networks","volume-title":"Proc. NeurIPS","volume":"21","author":"Jain"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/TIP.2017.2662206"},{"key":"ref24","first-page":"2802","article-title":"Image restoration using very deep convolutional encoder\u2013decoder networks with symmetric skip connections","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"29","author":"Mao"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.1109\/ICCV.2017.486"},{"key":"ref26","first-page":"1","article-title":"Non-local recurrent network for image restoration","volume-title":"Proc. NeurIPS","author":"Liu"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1109\/CVPRW.2018.00121"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.1109\/CVPR.2019.00181"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1109\/ICCV.2019.00325"},{"key":"ref30","first-page":"1","article-title":"Variational denoising network: Toward blind noise modeling and removal","volume-title":"Proc. NeurIPS","author":"Yue"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1007\/978-3-030-58607-2_3"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1007\/978-3-030-58595-2_30"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1109\/CVPR42600.2020.00354"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1109\/CVPR46437.2021.01458"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1109\/TPAMI.2021.3096255"},{"doi-asserted-by":"publisher","key":"ref36","DOI":"10.1109\/CVPR46437.2021.01184"},{"doi-asserted-by":"publisher","key":"ref37","DOI":"10.5244\/C.30.87"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.1109\/CVPR46437.2021.00098"},{"key":"ref39","first-page":"527","article-title":"Adaptive neural networks for efficient inference","volume-title":"Proc. ICML","author":"Bolukbasi"},{"key":"ref40","first-page":"2178","article-title":"Runtime neural pruning","volume-title":"Proc. NeurIPS","author":"Lin"},{"doi-asserted-by":"publisher","key":"ref41","DOI":"10.24963\/ijcai.2019\/416"},{"key":"ref42","first-page":"1","article-title":"AutoSlim: Towards one-shot architecture search for channel numbers","volume-title":"Proc. NeurIPS Workshop","author":"Yu"},{"key":"ref43","first-page":"1","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","volume-title":"Proc. ICLR","author":"Komodakis"},{"key":"ref44","first-page":"1","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. NeurIPS","author":"Tarvainen"},{"doi-asserted-by":"publisher","key":"ref45","DOI":"10.1145\/3097983.3098135"},{"doi-asserted-by":"publisher","key":"ref46","DOI":"10.1109\/CVPR.2018.00745"},{"doi-asserted-by":"publisher","key":"ref47","DOI":"10.1109\/CVPR42600.2020.01181"},{"doi-asserted-by":"publisher","key":"ref48","DOI":"10.1109\/CVPR.2018.00182"},{"doi-asserted-by":"publisher","key":"ref49","DOI":"10.1109\/CVPR.2017.294"},{"doi-asserted-by":"publisher","key":"ref50","DOI":"10.1109\/TIP.2018.2839891"},{"doi-asserted-by":"publisher","key":"ref51","DOI":"10.1007\/978-3-030-58577-8_11"},{"doi-asserted-by":"publisher","key":"ref52","DOI":"10.1109\/TPAMI.2022.3167175"},{"doi-asserted-by":"publisher","key":"ref53","DOI":"10.1109\/CVPR.2019.00406"},{"doi-asserted-by":"publisher","key":"ref54","DOI":"10.1109\/CVPR.2019.00613"},{"doi-asserted-by":"publisher","key":"ref55","DOI":"10.1109\/CVPR46437.2021.00352"},{"key":"ref56","first-page":"9782","article-title":"DynaBERT: Dynamic bert with adaptive width and depth","volume-title":"Proc. NeurIPS","volume":"33","author":"Hou"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/9991910\/10054501.pdf?arnumber=10054501","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T15:11:11Z","timestamp":1707837071000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10054501\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":56,"URL":"https:\/\/doi.org\/10.1109\/tip.2023.3246792","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"type":"print","value":"1057-7149"},{"type":"electronic","value":"1941-0042"}],"subject":[],"published":{"date-parts":[[2023]]}}}