{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:59:45Z","timestamp":1777705185568,"version":"3.51.4"},"reference-count":2,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2024,4,18]]},"abstract":"<jats:p>Person re-identification relies on discriminative features. However, most researches focus on extracting features from the high-layer of network while ignoring the middle-layer features, some important details are overlooked frequently. To address this issue, we propose a Multi-Scale and Multi-Patch Feature Fusion Network(MSPF). We employ modified OSFA to extract, align, and fuse the feature maps in the middle-layer of network, which can compensate for the lack of detailed information in the high-level network features. To obtain richer detailed global features of pedestrian, we construct a multi-patch feature fusion module(MPF). We concatenate the global features extracted from modified OSFA and MPF to obtain global features with richer detailed representations. Cross-entropy loss, triplet loss and center loss are combined to constrain our model. We evaluate the performance of our model on Market-1501, CUHK03_labeled and DukeMTMC. The results prove that our method is superior to the state-of-the-art approaches.<\/jats:p>","DOI":"10.3233\/jifs-237113","type":"journal-article","created":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T13:04:57Z","timestamp":1707224697000},"page":"7603-7612","source":"Crossref","is-referenced-by-count":0,"title":["Multi-scale and multi-patch feature fusion network for person re-identification"],"prefix":"10.1177","volume":"46","author":[{"given":"Yanqiu","family":"Wu","sequence":"first","affiliation":[{"name":"Minnan University of Science and Technology, Quanzhou, Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Liu","sequence":"additional","affiliation":[{"name":"Minnan University of Science and Technology, Quanzhou, Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dehong","family":"Sun","sequence":"additional","affiliation":[{"name":"Minnan University of Science and Technology, Quanzhou, Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"6","key":"10.3233\/JIFS-237113_ref23","doi-asserted-by":"crossref","first-page":"5987","DOI":"10.3233\/JIFS-212656","article-title":"Learning discriminative and generalizable features with multi-branch for person reidentification[J\/OL]","volume":"42","author":"Cheng","year":"2022","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-237113_ref25","doi-asserted-by":"publisher","DOI":"10.1109\/icpr48806.2021.9412598"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-237113","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:43:08Z","timestamp":1777455788000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-237113"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,18]]},"references-count":2,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/jifs-237113","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,18]]}}}