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This paper proposes an ArcFace SE-attention model-agnostic meta-learning approach (AS-MAML) by integrating attention mechanisms into residual networks for pedestrian gait recognition using frequency-modulated continuous-wave (FMCW) millimeter-wave radar through meta-learning. We enhance the feature extraction capability of the base network using channel attention mechanisms and integrate the additive angular margin loss function (ArcFace loss) into the inner loop of MAML to constrain inner loop optimization and improve radar discrimination. Then, this network is used to classify small-sample micro-Doppler images obtained from millimeter-wave radar as the data source for pose recognition. Experimental tests were conducted on pose estimation and image classification tasks. The results demonstrate significant detection and recognition performance, with an accuracy of 94.5%, accompanied by a 95% confidence interval. Additionally, on the open-source dataset DIAT-\u03bcRadHAR, which is specially processed to increase classification difficulty, the network achieves a classification accuracy of 85.9%.<\/jats:p>","DOI":"10.3390\/s24092932","type":"journal-article","created":{"date-parts":[[2024,5,6]],"date-time":"2024-05-06T14:26:11Z","timestamp":1715005571000},"page":"2932","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Pedestrian Pose Recognition Based on Frequency-Modulated Continuous-Wave Radar with Meta-Learning"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3609-0258","authenticated-orcid":false,"given":"Jiajia","family":"Shi","sequence":"first","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quan","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liu","family":"Chu","sequence":"additional","affiliation":[{"name":"Center for Transformative Science, ShanghaiTech University, Shanghai 201210, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4153-8769","authenticated-orcid":false,"given":"Robin","family":"Braun","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2050, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Heuer, M., Al-Hamadi, A., Rain, A., Meinecke, M.-M., and Rohling, H. 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