{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T09:22:05Z","timestamp":1781688125719,"version":"3.54.5"},"reference-count":47,"publisher":"IOP Publishing","issue":"4","license":[{"start":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T00:00:00Z","timestamp":1761782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T00:00:00Z","timestamp":1761782400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["RS-2023-00257994"],"award-info":[{"award-number":["RS-2023-00257994"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Mach. 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To enhance efficiency, we leveraged the advantages of the QAOA-incorporated parameter-shift rule to identify an optimized cost function, facilitating effective learning from data and gradient computation on an actual quantum computer. The proposed QCAE method outperformed its classical counterpart as it exhibited lower training loss and a higher structural similarity index (SSIM) value. QCAE also outperformed its classical counterpart in denoising the MNIST dataset by up to 40% in terms of SSIM value, confirming its enhanced capabilities in real-world applications. Evaluation of QAOA performance across different circuit configurations and layer variations showed that our technique outperformed other circuit designs by 25% on average.<\/jats:p>","DOI":"10.1088\/2632-2153\/ae1656","type":"journal-article","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T22:52:14Z","timestamp":1761173534000},"page":"045027","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Enhancing a convolutional autoencoder with a quantum approximate optimization algorithm for image noise reduction"],"prefix":"10.1088","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5240-015X","authenticated-orcid":true,"given":"Tara","family":"Kit","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8391-3869","authenticated-orcid":false,"given":"Kimsay","family":"Pov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6236-1379","authenticated-orcid":false,"given":"Kimleang","family":"Kea","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7437-4211","authenticated-orcid":false,"given":"Won-Du","family":"Chang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2064-1481","authenticated-orcid":false,"given":"Hee","family":"Chul Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7712-2514","authenticated-orcid":true,"given":"Youngsun","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2025,10,30]]},"reference":[{"key":"mlstae1656bib1","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.bspc.2018.01.010","type":"journal-article","volume":"42","author":"Diwakar","year":"2018","journal-title":"Biomed. 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