{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T15:07:28Z","timestamp":1784214448761,"version":"3.55.0"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3096240","type":"journal-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T20:34:53Z","timestamp":1626122093000},"page":"99742-99755","source":"Crossref","is-referenced-by-count":61,"title":["Fusion of Handcrafted and Deep Features for Forgery Detection in Digital Images"],"prefix":"10.1109","volume":"9","author":[{"given":"Savita","family":"Walia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Krishan","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Munish","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Zhi","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"ImageNet classification with deep convolutional neural networks","volume":"60","author":"krizhevsky","year":"2012","journal-title":"Commun ACM"},{"key":"ref33","article-title":"Wasserstein CNN: Learning invariant features for NIR-VIS face recognition","author":"he","year":"2017","journal-title":"arXiv 1708 02412"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2778011"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2016.2611485"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2725580"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2844175"},{"key":"ref35","first-page":"213","article-title":"FuseNet: Incorporating depth into semantic segmentation via fusion-based CNN architecture","volume":"10111","author":"hazirbas","year":"2017","journal-title":"Computer Vision"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2572683"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2012.05.014"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.25.2.023031"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.251"},{"key":"ref2","first-page":"55","article-title":"Detection of copy-move forgery in digital images","author":"fridrich","year":"2003","journal-title":"Proc Digital Forensic Res Workshop"},{"key":"ref1","first-page":"1103","article-title":"Study of image splicing detection","volume":"5226","author":"zhang","year":"2008","journal-title":"Adv Intell Comput Theor Appl With Asp Theor Methodol"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-016-0043-6"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2014.2347513"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-014-0396-4"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-017-1668-8"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-169261"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-2738-3_27"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"78","DOI":"10.5815\/ijigsp.2015.10.08","article-title":"Image forgery detection using multi scale entropy filter and local phase quantization","volume":"10","author":"agarwal","year":"2015","journal-title":"Int J Image Graph Signal Process"},{"key":"ref50","author":"kantor","year":"1989","journal-title":"Hypercomplex Numbers an Elementary Introduction to Algebras"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-4-431-53868-4_40"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ChinaSIP.2013.6625374"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.02.024"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2019.09.002"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/INISTA.2014.6873618"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.14257\/ijmue.2016.11.4.05"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1049\/iet-ipr.2017.0441"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2007.4285009"},{"key":"ref40","article-title":"Deep learning using rectified linear units (ReLU)","author":"fred agarap","year":"2018","journal-title":"arXiv 1803 08375"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2009.4959768"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s11760-016-0899-0"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICET.2015.7389169"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.image.2015.08.008","article-title":"A bibliography of pixel-based blind image forgery detection techniques","volume":"39","author":"ali","year":"2015","journal-title":"Signal Process Image Commun"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/WIFS.2014.7084318"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2014.7026073"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/EBBT.2019.8741657"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSDET.2018.8821242"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2008.931079"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2004.839896"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1080\/00450618.2018.1424241"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-007-0154-3"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2017.04.004"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2011.2129512"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2003.812734"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2016.12.022"},{"key":"ref46","first-page":"1","article-title":"Image region forgery detection: A deep learning approach","volume":"14","author":"zhang","year":"2016","journal-title":"Proc Singap Cyber-Secur Conf"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/WIFS.2016.7823911"},{"key":"ref48","first-page":"1","article-title":"Quaternions and rotations","author":"barbic","year":"2011"},{"key":"ref47","first-page":"1","article-title":"Combining deep and handcrafted image features for presentation attack detection in face recognition systems using visible-light camera sensors","volume":"18","author":"nguyen","year":"2018","journal-title":"SENSORS"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ACPR.2015.7486599"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.3390\/info11050275"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09481119.pdf?arnumber=9481119","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,5]],"date-time":"2023-11-05T23:20:29Z","timestamp":1699226429000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9481119\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":56,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3096240","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}