{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T22:55:42Z","timestamp":1761519342020},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2022,4,10]],"date-time":"2022-04-10T00:00:00Z","timestamp":1649548800000},"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":[[2023,7,13]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Most of research studies that have dealt with face corrupted images to the level of being unrecognizable by a human are based on full image reconstruction. In some real scenarios, a single corrupted image might need to be recognized among a limited number of available clean images. This study deals with face identification from artificially corrupted images with various kinds of noises. The work proposes a face identification conditional generative adversarial network (FI-CGAN) model to identify faces based on the CGAN. The proposed models reconstruct the corrupted image based on available clean images to map the corrupted image to a specific label. The classification is made using the nearest neighbor method with peak signal-to-noise ratio, mean squared error and structural similarity index as metrics. The study used the Specs on Faces dataset and achieved a satisfactory performance for face identification.<\/jats:p>","DOI":"10.1093\/comjnl\/bxac034","type":"journal-article","created":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T20:10:29Z","timestamp":1647375029000},"page":"1687-1697","source":"Crossref","is-referenced-by-count":2,"title":["Face Identification Using Conditional Generative Adversarial Network"],"prefix":"10.1093","volume":"66","author":[{"given":"Samer","family":"Kais Jameel","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Raparin , Rania, Kurdistan Region , Iraq"}]},{"given":"Jafar","family":"Majidpour","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Raparin , Rania, Kurdistan Region , Iraq"}]},{"given":"Abdulbasit K","family":"Al-Talabani","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, Faculty of Engineering, Koya University , Koya KOY45, Kurdistan Region - F.R. 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