{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T16:19:48Z","timestamp":1781194788173,"version":"3.54.1"},"reference-count":57,"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\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U20B2072"],"award-info":[{"award-number":["U20B2072"]}],"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":["61976137"],"award-info":[{"award-number":["61976137"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Jiaotong University Medical Engineering Cross Research","award":["YG2021ZD18"],"award-info":[{"award-number":["YG2021ZD18"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tmm.2021.3124095","type":"journal-article","created":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T21:21:38Z","timestamp":1635888098000},"page":"214-227","source":"Crossref","is-referenced-by-count":20,"title":["Residual Quantization for Low Bit-Width Neural Networks"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0404-8856","authenticated-orcid":false,"given":"Zefan","family":"Li","sequence":"first","affiliation":[{"name":"Shanghi Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7339-028X","authenticated-orcid":false,"given":"Bingbing","family":"Ni","sequence":"additional","affiliation":[{"name":"Shanghi Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4029-3322","authenticated-orcid":false,"given":"Xiaokang","family":"Yang","sequence":"additional","affiliation":[{"name":"Shanghi Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8799-1182","authenticated-orcid":false,"given":"Wenjun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghi Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8070-802X","authenticated-orcid":false,"given":"Wen","family":"Gao","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"856","article-title":"Compression-aware training of deep networks","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Alvarez","year":"2017"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2016-128"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2922130"},{"key":"ref4","first-page":"7948","article-title":"Post training 4-bit quantization of convolutional networks for rapid-deployment","volume-title":"Adv. Neural Inf. Process. Syst.","author":"Banner","year":"2019"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1150402.1150464"},{"key":"ref6","article-title":"High-capacity expert binary networks","volume-title":"9th Int. Conf. Learning Representations","author":"Bulat","year":"2021"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2846405"},{"key":"ref8","article-title":"Bridging the accuracy gap for 2-bit quantized neural networks (QNN)","author":"Choi","year":"2018"},{"key":"ref9","article-title":"PACT: parameterized clipping activation for quantized neural networks","author":"Choi","year":"2018"},{"key":"ref10","first-page":"3123","article-title":"Binaryconnect: Training deep neural networks with binary weights during propagations","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Courbariaux","year":"2015"},{"key":"ref11","first-page":"1269","article-title":"Exploiting linear structure within convolutional networks for efficient evaluation","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Denton","year":"2014"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2017.00021"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.2975961"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.430"},{"key":"ref15","article-title":"Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding","author":"Han","year":"2016","journal-title":"4th Int. Conf. Learning Representations"},{"key":"ref16","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Han","year":"2015"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.155"},{"key":"ref19","article-title":"Distilling the knowledge in a neural network","volume-title":"Proc. NeurIPS Workshop Deep Learn. Representation","author":"Hinton","year":"2014"},{"key":"ref20","article-title":"Network trimming: A data-driven neuron pruning approach towards efficient deep architectures","volume-title":"CoRR","author":"Hu","year":"2016"},{"key":"ref21","article-title":"Binarized neural networks,","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","volume":"29","author":"Hubara","year":"2016"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00286"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.5244\/c.28.88"},{"key":"ref24","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref27","article-title":"Ternary weight networks,","volume-title":"CoRR","author":"Li","year":"2016"},{"key":"ref28","article-title":"Pruning filters for efficient convnets","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Li","year":"2017"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2017EDL8248"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.282"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2873305"},{"key":"ref32","first-page":"345","article-title":"Towards accurate binary convolutional neural network","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Lin","year":"2017"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01267-0_44"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2014.2360798"},{"key":"ref35","article-title":"Training binary neural networks with real-to-binary convolutions","volume-title":"8th Int. Conf. Learning Representations","author":"Martinez","year":"2020"},{"key":"ref36","article-title":"Wide reduced-precision networks","volume-title":"6th Int. Conf. Learning Representations","author":"Mishra","year":"2018"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.2118\/18761-MS"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_32"},{"key":"ref39","article-title":"Fitnets: Hints for thin deep nets","volume-title":"3rd Int. Conf. Learning Representations","author":"Romero","year":"2015"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178838"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2343229"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2392779"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.4324\/9781410605337-29"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2922129"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/384"},{"key":"ref47","first-page":"9847","article-title":"Towards accurate post-training network quantization via bit-split and stitching","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Wang","year":"2020"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2950523"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2949857"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2014.2375793"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-27529-7_29"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298809"},{"key":"ref53","article-title":"Incremental network quantization: Towards lossless CNNs with low-precision weights","volume-title":"5th Int. Conf. Learning Representations","author":"Zhou","year":"2017"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00982"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_40"},{"key":"ref56","article-title":"Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients","volume-title":"CoRR","author":"Zhou","year":"2016"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.2969791"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/10016790\/09599561.pdf?arnumber=9599561","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T02:14:48Z","timestamp":1705025688000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9599561\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/tmm.2021.3124095","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}