{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T09:49:10Z","timestamp":1767260950449,"version":"3.37.3"},"reference-count":70,"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-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100018058","name":"SK hynix Inc","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100018058","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3272665","type":"journal-article","created":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T18:51:42Z","timestamp":1683139902000},"page":"44895-44910","source":"Crossref","is-referenced-by-count":8,"title":["PyNET-Q\u00d7Q: An Efficient PyNET Variant for Q\u00d7Q Bayer Pattern Demosaicing in CMOS Image Sensors"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2230-4473","authenticated-orcid":false,"given":"Minhyeok","family":"Cho","sequence":"first","affiliation":[{"name":"Department of Electronic and Electrical Engineering, Hongik University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haechang","family":"Lee","sequence":"additional","affiliation":[{"name":"SK hynix, Icheon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8014-0393","authenticated-orcid":false,"given":"Hyunwoo","family":"Je","sequence":"additional","affiliation":[{"name":"SK hynix, Icheon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kijeong","family":"Kim","sequence":"additional","affiliation":[{"name":"SK hynix, Icheon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongil","family":"Ryu","sequence":"additional","affiliation":[{"name":"SK hynix, Icheon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6346-4182","authenticated-orcid":false,"given":"Albert","family":"No","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering, Hongik University, Seoul, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2803341"},{"key":"ref57","article-title":"Local-selective feature distillation for single image super-resolution","author":"park","year":"2021","journal-title":"arXiv 2111 10988"},{"key":"ref12","first-page":"6","article-title":"Color image demosaicking via deep residual learning","author":"tan","year":"2017","journal-title":"Proc ICME"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP40778.2020.9190917"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"key":"ref59","article-title":"Compressing GANs using knowledge distillation","author":"aguinaldo","year":"2019","journal-title":"arXiv 1902 00159"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00231"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58586-0_28"},{"key":"ref53","first-page":"12345","article-title":"Agree to disagree: Adaptive ensemble knowledge distillation in gradient space","author":"du","year":"2020","journal-title":"Proc NIPS"},{"key":"ref52","first-page":"1","article-title":"Knowledge distillation by on-the-fly native ensemble","author":"zhu","year":"2018","journal-title":"Proc NIPS"},{"key":"ref11","first-page":"1","article-title":"Distilling the knowledge in a neural network","author":"hinton","year":"2015","journal-title":"Proc NIPS Workshop"},{"key":"ref55","first-page":"527","article-title":"Image super-resolution using knowledge distillation","author":"gao","year":"2018","journal-title":"Proc ACCV"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.23915\/distill.00003"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.07.048"},{"key":"ref17","article-title":"Joint demosaicing and denoising with perceptual optimization on a generative adversarial network","author":"dong","year":"2018","journal-title":"arXiv 1802 04723"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2980179.2982399"},{"key":"ref19","article-title":"Learning deep convolutional networks for demosaicing","author":"syu","year":"2018","journal-title":"arXiv 1802 03769"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_19"},{"key":"ref51","first-page":"2006","article-title":"Feature-map-level online adversarial knowledge distillation","author":"chung","year":"2020","journal-title":"Proc ICML"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01103"},{"key":"ref46","first-page":"1","article-title":"FitNets: Hints for thin deep nets","author":"romero","year":"2014","journal-title":"Proc ICLR"},{"key":"ref45","article-title":"Pro-KD: Progressive distillation by following the footsteps of the teacher","author":"rezagholizadeh","year":"2021","journal-title":"arXiv 2110 08532"},{"key":"ref48","article-title":"Large scale distributed neural network training through online distillation","author":"anil","year":"2018","journal-title":"arXiv 1804 03235"},{"key":"ref47","first-page":"1","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","author":"zagoruyko","year":"2017","journal-title":"Proc ICLR"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"ref41","first-page":"1","article-title":"An image is worth 16&#x00D7;16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2021","journal-title":"Proc ICLR"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00489"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00545"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5746"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00583"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.207"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00282"},{"key":"ref3","article-title":"Del-Net: A single-stage network for mobile camera ISP","author":"gupta","year":"2021","journal-title":"arXiv 2108 01623"},{"key":"ref6","first-page":"1","article-title":"On recent results in demosaicing of Samsung 108 MP CMOS sensor using deep learning","author":"kim","year":"2021","journal-title":"Proc IEEE Region Symp (TENSYMP)"},{"key":"ref5","article-title":"SAGAN: Adversarial spatial-asymmetric attention for noisy Nona-Bayer reconstruction","author":"sharif","year":"2021","journal-title":"arXiv 2110 08619"},{"key":"ref40","first-page":"63","article-title":"ESRGAN: Enhanced super-resolution generative adversarial networks","author":"wang","year":"2018","journal-title":"Proc ECC"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.181"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2662206"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.300"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_25"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3390462"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-67070-2_12"},{"key":"ref33","first-page":"1","article-title":"Image super-resolution using gradient profile prior","author":"sun","year":"2008","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"1127","DOI":"10.1109\/TPAMI.2010.25","article-title":"Single-image super-resolution using sparse regression and natural image prior","volume":"32","author":"kim","year":"2010","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-67070-2_10"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00276"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.182"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_16"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00032"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.161"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.2352\/J.ImagingSci.Technol.2019.63.6.060410"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2631888"},{"key":"ref26","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc MICCAI"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-67070-2_9"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CAC.2017.8243724"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1017\/ATSIP.2019.2"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2008.2002164"},{"key":"ref66","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc ICLR"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2005.1561853"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3051486"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00448"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2872858"},{"key":"ref60","first-page":"1","article-title":"KDGAN: Knowledge distillation with generative adversarial networks","author":"wang","year":"2018","journal-title":"Proc NIPS"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00071"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/ISOCC53507.2021.9614015"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10114931.pdf?arnumber=10114931","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T02:09:30Z","timestamp":1733882970000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10114931\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":70,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3272665","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2023]]}}}