{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T19:23:02Z","timestamp":1779909782691,"version":"3.53.1"},"reference-count":54,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Bialystok University of Technology, Poland"},{"name":"Ministry of Science and Higher Education in Poland. During the progress of the research work, the authors got funding support from Visvesvaraya Ph.D. Scheme, Ministry of Electronics and IT, India"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.3006100","type":"journal-article","created":{"date-parts":[[2020,6,30]],"date-time":"2020-06-30T20:49:59Z","timestamp":1593550199000},"page":"123556-123570","source":"Crossref","is-referenced-by-count":12,"title":["A Granular Level Feature Extraction Approach to Construct HR Image for Forensic Biometrics Using Small Training DataSet"],"prefix":"10.1109","volume":"8","author":[{"given":"Khalid","family":"Saeed","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3698-6521","authenticated-orcid":false,"given":"Soma","family":"Datta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3242-680X","authenticated-orcid":false,"given":"Nabendu","family":"Chaki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.irbm.2019.10.005"},{"key":"ref38","author":"mooney","year":"2018","journal-title":"Kaggle Database Chest X-Ray Images (Pneumonia)"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/566654.566573"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1364\/JOSA.61.000001"},{"key":"ref31","author":"horn","year":"1986","journal-title":"Robot Vision"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s41666-017-0009-2"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2013.03.020"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2235848"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.244"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"1635","DOI":"10.1109\/TIP.2010.2042645","article-title":"Enhanced local texture feature sets for face recognition under difficult lighting conditions","volume":"19","author":"tan","year":"2010","journal-title":"IEEE Trans Image Process"},{"key":"ref28","article-title":"MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs","author":"johnson","year":"2019","journal-title":"arXiv 1901 07042"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2015.2421314"},{"key":"ref29","year":"2015","journal-title":"Digital Dental Periapical X-Ray Database for Caries Screening Digital Dental X-Ray Image Dataset Along Ground Truth"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/9781119544487.ch6"},{"key":"ref1","year":"2019","journal-title":"Global Study on Homicide 2019"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s11045-007-0018-z"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IVCNZ.2010.6148792"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2005.846647"},{"key":"ref24","year":"2008","journal-title":"National Institute of Standards and Technology Multiple Biometric Grandchallenge (MBGT)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2011.2159597"},{"key":"ref26","first-page":"623","article-title":"Improving video-based iris recognition via local quality weighted super resolution","author":"othman","year":"2013","journal-title":"Proc ICPR"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2889395"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2108306"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/BMSB.2016.7521905"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.irbm.2019.04.001"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/s42979-020-0066-0"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2015.12.038"},{"key":"ref10","first-page":"239","article-title":"Image interpolation by super-resolution","author":"lukin","year":"2006","journal-title":"Proc GraphiCon"},{"key":"ref11","first-page":"1","article-title":"Review of image interpolation and super-resolution","author":"siu","year":"2012","journal-title":"Proc Asia Pacific Signal Inf Process Assoc Annu Summit Conf"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(02)00616-1"},{"key":"ref12","first-page":"1","article-title":"Super-resolution through neighbor embedding","volume":"1","author":"chang","year":"2004","journal-title":"Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2189576"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.taml.2016.04.003"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/1049-9652(92)90065-6"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.1261081"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2028255"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459271"},{"key":"ref19","first-page":"135","article-title":"Kernel hebbian algorithm for single-frame super-resolution","author":"kim","year":"2004","journal-title":"Proc Workshop Statistical Learning in Computer Vision"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-56499-8_7"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10593-2_25"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2050625"},{"key":"ref5","first-page":"374","article-title":"Super-resolution from image sequences–A review","author":"borman","year":"1998","journal-title":"Proc Midwest Symp Circuits Syst"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/1049-9652(91)90045-L"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2005.860355"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.141"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/BF01200891"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2109730"},{"key":"ref45","author":"datta","year":"2020","journal-title":"LR to HR Image Reconstruction"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.aqpro.2015.02.019"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2481319"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"key":"ref41","first-page":"913","article-title":"Application of ridge polynomial neural networks to financial time series prediction","author":"ghazali","year":"2006","journal-title":"Proc IEEE Int Joint Conf Neural Netw"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00130"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11021-5_20"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09129655.pdf?arnumber=9129655","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T01:09:48Z","timestamp":1641949788000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9129655\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3006100","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}