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The experimental results showed that the accuracy of the proposed model was improved by 9.36%, and the communication cost was reduced by 1.45 times compared with state-of-the-art models. Last but not least, we deploy flower identification models in Android Studio to illustrate the practicality of the proposed method.<\/jats:p>","DOI":"10.1007\/s40747-023-01332-9","type":"journal-article","created":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T04:14:30Z","timestamp":1707711270000},"page":"3577-3592","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A lightweight and personalized edge federated learning model"],"prefix":"10.1007","volume":"10","author":[{"given":"Peiyan","family":"Yuan","sequence":"first","affiliation":[]},{"given":"Ling","family":"Shi","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7525-6244","authenticated-orcid":false,"given":"Xiaoyan","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Junna","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,12]]},"reference":[{"key":"1332_CR1","unstructured":"Ben\u00a0Mansour A, Carenini G, Duplessis A (2023) Tackling computational heterogeneity in fl: A few theoretical insights. arXiv e-prints, 2307"},{"issue":"6","key":"1332_CR2","doi-asserted-by":"publisher","first-page":"4889","DOI":"10.1007\/s00521-021-06679-z","volume":"34","author":"T Choudhary","year":"2022","unstructured":"Choudhary T, Mishra V, Goswami A, Sarangapani J (2022) Heuristic-based automatic pruning of deep neural networks. 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