{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T06:08:49Z","timestamp":1774418929110,"version":"3.50.1"},"reference-count":52,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T00:00:00Z","timestamp":1633392000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Presently, facial image recognition via a thermal camera is a critical phase in numerous fields. Systems using thermal facial images suffer from numerous problems in face identification. In this paper, a model Edge-Aided Generative Adversarial Network (EA-GAN) is introduced to overcome the difficulties of thermal face identification by synthesizing a visible faces image from the thermal version. To enhance the performance of the Conditional Generative Adversarial Network (CGAN) model for the create realistic face images, the edge information extracted from the thermal image has been used as input, thus lead to improving overall the system's achievement. Moreover, a new model is presented in the present work for face identification by integrating two Convolutional Neural Networks (CNN) to achieve high and rapid accuracy rates. Based on the experiments on the Carl dataset for faces, it is indicated that EA-GAN can synthesize visually comfortable and identity-preserving faces; thus, better performance is achieved in comparison with the state-of-the-art approaches for thermal facial identification.<\/jats:p>","DOI":"10.1093\/comjnl\/bxab144","type":"journal-article","created":{"date-parts":[[2021,9,12]],"date-time":"2021-09-12T11:06:56Z","timestamp":1631444816000},"page":"61-69","source":"Crossref","is-referenced-by-count":6,"title":["Face Identification System Based on Synthesizing Realistic Image using Edge-Aided GANs"],"prefix":"10.1093","volume":"66","author":[{"given":"Jafar","family":"Majidpour","sequence":"first","affiliation":[{"name":"Department of Computer Science , University of Raparin, Rania, Kurdistan Region, Iraq"}]},{"given":"Samer","family":"Kais Jameel","sequence":"additional","affiliation":[{"name":"Department of Computer Science , University of Raparin, Rania, Kurdistan Region, Iraq"}]},{"given":"Jihad","family":"Anwar Qadir","sequence":"additional","affiliation":[{"name":"Department of Computer Science , University of Raparin, Rania, Kurdistan Region, Iraq"}]}],"member":"286","published-online":{"date-parts":[[2021,10,5]]},"reference":[{"issue":"4-5","key":"2023011814194264000_ref1","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1016\/S0264-3707(02)00013-3","article-title":"Thermal IR satellite data application for earthquake research in Japan and China","volume":"33","author":"Tronin","year":"2002","journal-title":"Journal of Geodynamics"},{"key":"2023011814194264000_ref2","doi-asserted-by":"crossref","DOI":"10.5772\/18986","article-title":"Thermal infrared face recognition a biometric identification technique for robust security system","volume-title":"Reviews, refinements and new ideas in face 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