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You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader. Continue Cancel clearAll articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess. Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications. Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers. Editor鈥檚 Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal. ![]() ![]() ![]() Find support for a specific problem in the support section of our website. Get Support FeedbackPlease let us know what you think of our products and services. Give Feedback InformationVisit our dedicated information section to learn more about MDPI. Get Information clear Open AccessArticle Article Versions Notes Healthcare 2023, 11(9), 1205; https://doi.org/10.3390/healthcare11091205 (registering DOI) Action Date Notes Link article xml file uploaded 23 April 2023 09:28 CEST Original file - article xml uploaded. 23 April 2023 09:28 CEST Update https://www.mdpi.com/2227-9032/11/9/1205/xml article pdf uploaded. 23 April 2023 09:28 CEST Version of Record https://www.mdpi.com/2227-9032/11/9/1205/pdf article html file updated 23 April 2023 09:29 CEST Original file https://www.mdpi.com/2227-9032/11/9/1205/html Cite Export citation file: BibTeX | EndNote | RIS MDPI and ACS StyleSun, Y.; Lou, W.; Ma, W.; Zhao, F.; Su, Z. Convolution Neural Network with Coordinate Attention for Real-Time Wound Segmentation and Automatic Wound Assessment. Healthcare 2023, 11, 1205. https://doi.org/10.3390/healthcare11091205 AMA StyleSun Y, Lou W, Ma W, Zhao F, Su Z. Convolution Neural Network with Coordinate Attention for Real-Time Wound Segmentation and Automatic Wound Assessment. Healthcare. 2023; 11(9):1205. https://doi.org/10.3390/healthcare11091205 Chicago/Turabian StyleSun, Yi, Wenzhong Lou, Wenlong Ma, Fei Zhao, and Zilong Su. 2023. "Convolution Neural Network with Coordinate Attention for Real-Time Wound Segmentation and Automatic Wound Assessment" Healthcare 11, no. 9: 1205. https://doi.org/10.3390/healthcare11091205 Find Other Styles Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here. clear Article Metrics No No Article metric data becomes available approximately 24 hours after publication online. clear Healthcare, EISSN 2227-9032, Published by MDPI RSS Content Alert Further Information Article Processing Charges Pay an Invoice Open Access Policy Contact MDPI Jobs at MDPI Guidelines For Authors For Reviewers For Editors For Librarians For Publishers For Societies For Conference Organizers MDPI Initiatives Sciforum MDPI Books Preprints.org Scilit SciProfiles Encyclopedia JAMS Proceedings Series Follow MDPI LinkedIn Facebook Twitter![]() |
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