{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:02:21Z","timestamp":1773414141678,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,3,6]],"date-time":"2018-03-06T00:00:00Z","timestamp":1520294400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672335"],"award-info":[{"award-number":["61672335"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61601276"],"award-info":[{"award-number":["61601276"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61302174"],"award-info":[{"award-number":["61302174"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61571380"],"award-info":[{"award-number":["61571380"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Fujian Province of China","award":["2016J05205"],"award-info":[{"award-number":["2016J05205"]}]},{"name":"high-level talents program of Xiamen University of Technology","award":["YKJ16018R"],"award-info":[{"award-number":["YKJ16018R"]}]},{"name":"high-level talents program of Xiamen University of Technology","award":["YKJ16020R"],"award-info":[{"award-number":["YKJ16020R"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/s18030789","type":"journal-article","created":{"date-parts":[[2018,3,6]],"date-time":"2018-03-06T12:16:27Z","timestamp":1520338587000},"page":"789","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6582-6423","authenticated-orcid":false,"given":"Xiaofeng","family":"Du","sequence":"first","affiliation":[{"name":"School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}]},{"given":"Xiaobo","family":"Qu","sequence":"additional","affiliation":[{"name":"Department of Electronic Science, Xiamen University, Xiamen 361005, China"}]},{"given":"Yifan","family":"He","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9910-5720","authenticated-orcid":false,"given":"Di","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1423","DOI":"10.1007\/s00138-014-0623-4","article-title":"Super-resolution: A comprehensive survey","volume":"25","author":"Nasrollahi","year":"2014","journal-title":"Mach. 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