{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T09:32:37Z","timestamp":1775381557508,"version":"3.50.1"},"reference-count":68,"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:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100002873","name":"Second Century Fund (C2F) Chulalongkorn University, Electrical Engineering Department, Bangkok, Thailand","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002873","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002873","name":"Thailand Science Research and Innovation Fund Chulalongkorn University","doi-asserted-by":"publisher","award":["CU_FRB65_ind (9)_157_21_23"],"award-info":[{"award-number":["CU_FRB65_ind (9)_157_21_23"]}],"id":[{"id":"10.13039\/501100002873","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002873","name":"Thailand Science Research and Innovation Fund Chulalongkorn University","doi-asserted-by":"publisher","award":["IND66210019"],"award-info":[{"award-number":["IND66210019"]}],"id":[{"id":"10.13039\/501100002873","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NSRF via the Program Management Unit for Human Resources and Institutional Development, Research and Innovation","award":["B04G640053"],"award-info":[{"award-number":["B04G640053"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3274679","type":"journal-article","created":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T23:51:57Z","timestamp":1683762717000},"page":"45989-46003","source":"Crossref","is-referenced-by-count":13,"title":["SENext: Squeeze-and-ExcitationNext for Single Image Super-Resolution"],"prefix":"10.1109","volume":"11","author":[{"given":"Wazir","family":"Muhammad","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Chulalongkorn University, Bangkok, Thailand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9840-3171","authenticated-orcid":false,"given":"Supavadee","family":"Aramvith","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Faculty of Engineering, Multimedia Data Analytics and Processing Unit, Chulalongkorn University, Bangkok, Thailand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1894-2448","authenticated-orcid":false,"given":"Takao","family":"Onoye","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Technology, Osaka University, Suita, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref57","first-page":"3859","article-title":"Dynamic routing between capsules","author":"sabour","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3390462"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-06953-8"},{"key":"ref15","first-page":"6","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"28","author":"maas","year":"2013","journal-title":"Proc 30th Int Conf Mach Learn"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.05.042"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2018.8546130"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.161"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2020.107567"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.181"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.207"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.09.049"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.50"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref19","first-page":"2802","article-title":"Image restoration using very deep convolutional encoder&#x2013;decoder networks with symmetric skip connections","author":"mao","year":"2016","journal-title":"Proc NIPS"},{"key":"ref18","first-page":"370","article-title":"Deeply improved sparse coding for image super-resolution","author":"wang","year":"2015","journal-title":"Proc IEEE Int Conf Comput Vis"},{"key":"ref51","article-title":"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and < 0.5 MB model size","author":"iandola","year":"2016","journal-title":"arXiv 1602 07360"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_18"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"15049","DOI":"10.1038\/s41598-017-15273-0","article-title":"A POCS super resolution restoration algorithm based on BM3D","volume":"7","author":"cheng","year":"2017","journal-title":"Sci Rep"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.09.035"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.05.066"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2022.104568"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-019-08218-4"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2929223"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2964292"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0249278"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.05.061"},{"key":"ref8","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_25"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.182"},{"key":"ref4","first-page":"111","article-title":"A+: Adjusted anchored neighborhood regression for fast super-resolution","author":"timofte","year":"2014","journal-title":"Proc Asian Conf Comput Vis (ACCV)"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.75"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299003"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00082"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3390\/electronics8080892"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00344"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2903582"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"1669","DOI":"10.1109\/TIP.2019.2941327","article-title":"Receptive field size versus model depth for single image super-resolution","volume":"29","author":"wang","year":"2020","journal-title":"IEEE Trans Image Process"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_32"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00178"},{"key":"ref33","article-title":"Lightweight and efficient image super-resolution with block state-based recursive network","author":"choi","year":"2018","journal-title":"arXiv 1811 12546"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_16"},{"key":"ref2","first-page":"1","article-title":"Image super-resolution as sparse representation of raw image patches","author":"yang","year":"2008","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2050625"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICMEW.2019.00108"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2863602"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.298"},{"key":"ref68","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351084"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CICT56698.2022.9997956"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2016.2629284"},{"key":"ref64","first-page":"683","article-title":"Detection of lung malignancy using SqueezeNet-Fc deep learning classification technique","author":"kumar","year":"2021","journal-title":"Proc Int Conf Paradigms Commun Comput Data Sci"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-4020-z"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2662206"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2022.100399"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.618"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.3390\/s19050982"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.486"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70096-0_23"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.5244\/C.26.135"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"ref61","first-page":"711","article-title":"On single image scale-up using sparse-representations","author":"zeyde","year":"2010","journal-title":"Proc Int Conf Curves Surf"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10121756.pdf?arnumber=10121756","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T18:18:27Z","timestamp":1686593907000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10121756\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":68,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3274679","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}