{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T01:31:46Z","timestamp":1779931906968,"version":"3.53.1"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61874107"],"award-info":[{"award-number":["61874107"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61704167"],"award-info":[{"award-number":["61704167"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2019YFB2204300"],"award-info":[{"award-number":["2019YFB2204300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009592","name":"Beijing Municipal Science and Technology Project","doi-asserted-by":"publisher","award":["Z181100008918009"],"award-info":[{"award-number":["Z181100008918009"]}],"id":[{"id":"10.13039\/501100009592","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Circuits Syst. Video Technol."],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1109\/tcsvt.2021.3071532","type":"journal-article","created":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T20:37:49Z","timestamp":1617827869000},"page":"1658-1666","source":"Crossref","is-referenced-by-count":26,"title":["Exploring Structural Sparsity in CNN via Selective Penalty"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5148-4218","authenticated-orcid":false,"given":"Mingxin","family":"Zhao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junbo","family":"Peng","sequence":"additional","affiliation":[{"name":"Nuclear and Radiological Engineering and Medical Physics Programs, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6678-3886","authenticated-orcid":false,"given":"Shuangming","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2585-323X","authenticated-orcid":false,"given":"Liyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8022-0262","authenticated-orcid":false,"given":"Nanjian","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref2","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref5","article-title":"Depthwise separable convolutions for neural machine translation","author":"Kaiser","year":"2017","journal-title":"arXiv:1706.03059"},{"key":"ref6","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Tan"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2018.2865896"},{"key":"ref8","article-title":"Learning sparse neural networks through L0 regularization","author":"Louizos","year":"2017","journal-title":"arXiv:1712.01312"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6910"},{"key":"ref10","article-title":"Neural architecture search with reinforcement learning","author":"Zoph","year":"2016","journal-title":"arXiv:1611.01578"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_2"},{"key":"ref12","article-title":"DARTS: Differentiable architecture search","author":"Liu","year":"2018","journal-title":"arXiv:1806.09055"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00332"},{"key":"ref14","article-title":"ProxylessNAS: Direct neural architecture search on target task and hardware","author":"Cai","year":"2018","journal-title":"arXiv:1812.00332"},{"key":"ref15","article-title":"Compressing deep neural networks with pruning, trained quantization and Huffman coding","author":"Han","year":"2015","journal-title":"arXiv:1510.00149"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_12"},{"key":"ref17","article-title":"Learning to prune deep neural networks via layer-wise optimal brain surgeon","author":"Dong","year":"2017","journal-title":"arXiv:1705.07565"},{"key":"ref18","article-title":"Learning both weights and connections for efficient neural networks","author":"Han","year":"2015","journal-title":"arXiv:1506.02626"},{"key":"ref19","article-title":"The lottery ticket hypothesis: Finding sparse, trainable neural networks","author":"Frankle","year":"2018","journal-title":"arXiv:1803.03635"},{"key":"ref20","first-page":"5544","article-title":"Soft threshold weight reparameterization for learnable sparsity","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kusupati"},{"key":"ref21","first-page":"2943","article-title":"Rigging the lottery: Making all tickets winners","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Evci"},{"key":"ref22","article-title":"Movement pruning: Adaptive sparsity by fine-tuning","author":"Sanh","year":"2020","journal-title":"arXiv:2005.07683"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA.2016.30"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3140659.3080254"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2016.7783723"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3352460.3358291"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3352460.3358275"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.541"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.298"},{"key":"ref30","article-title":"Discrimination-aware channel pruning for deep neural networks","author":"Zhuang","year":"2018","journal-title":"arXiv:1810.11809"},{"key":"ref31","article-title":"Gate decorator: Global filter pruning method for accelerating deep convolutional neural networks","author":"You","year":"2019","journal-title":"arXiv:1909.08174"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00289"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00447"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00161"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3035028"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3045153"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2021.3054315"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6720"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00290"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.03.056"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/480"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_18"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_48"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00339"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/309"},{"key":"ref46","article-title":"Pruning filters for efficient ConvNets","author":"Li","year":"2016","journal-title":"arXiv:1608.08710"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00804"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58580-8_35"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.l007\/978-3-319-46448-0_2"},{"key":"ref50","article-title":"Pelee: A real-time object detection system on mobile devices","author":"Wang","year":"2018","journal-title":"arXiv:1804.06882"},{"key":"ref51","volume-title":"Google Edge TPU","year":"2021"},{"key":"ref52","article-title":"Network trimming: A data-driven neuron pruning approach towards efficient deep architectures","author":"Hu","year":"2016","journal-title":"arXiv:1607.03250"}],"container-title":["IEEE Transactions on Circuits and Systems for Video Technology"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/76\/9730812\/09398648.pdf?arnumber=9398648","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:54:01Z","timestamp":1704844441000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9398648\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3]]},"references-count":52,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tcsvt.2021.3071532","relation":{},"ISSN":["1051-8215","1558-2205"],"issn-type":[{"value":"1051-8215","type":"print"},{"value":"1558-2205","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3]]}}}