{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T11:44:03Z","timestamp":1765453443668,"version":"3.46.0"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,9,3]]},"DOI":"10.1145\/3748699.3749791","type":"proceedings-article","created":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T07:01:29Z","timestamp":1765350089000},"page":"194-199","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Lightweight Uni-Domain Model for Human Activity Recognition Using UWB Radars"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2028-144X","authenticated-orcid":false,"given":"Shadi","family":"Abudalfa","sequence":"first","affiliation":[{"name":"SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRC-AI), King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5227-6602","authenticated-orcid":false,"given":"Kevin","family":"Bouchard","sequence":"additional","affiliation":[{"name":"Laboratoire d'Intelligence Ambiante pour la Reconnaissance d'Activit\u00e9s (LIARA), Universit\u00e9 du Qu\u00e9bec \u00e0 Chicoutimi, Saguenay, Canada"}]}],"member":"320","published-online":{"date-parts":[[2025,12,9]]},"reference":[{"key":"e_1_3_3_2_2_2","unstructured":"Alaaeldin Ali Hugo Touvron Mathilde Caron Piotr Bojanowski Matthijs Douze Armand Joulin Ivan Laptev Natalia Neverova Gabriel Synnaeve Jakob Verbeek et\u00a0al. 2021. Xcit: Cross-covariance image transformers. Advances in neural information processing systems 34 (2021) 20014\u201320027."},{"key":"e_1_3_3_2_3_2","doi-asserted-by":"crossref","unstructured":"Mohammad Belal Taimur Hassan Abdelfatah Hassan Divya Velayudhan Noureldin Elhendawi and Irfan Hussain. 2025. FSID: A Novel Approach to Human Activity Recognition Using Few-Shot Weight Imprinting. (2025).","DOI":"10.21203\/rs.3.rs-5752651\/v1"},{"key":"e_1_3_3_2_4_2","doi-asserted-by":"crossref","unstructured":"Minhao Ding Guangxin Dongye Ping Lv and Yipeng Ding. 2024. FML-Vit: A Lightweight Vision Transformer Algorithm for Human Activity Recognition Using FMCW Radar. IEEE Sensors Journal (2024).","DOI":"10.1109\/JSEN.2024.3473890"},{"key":"e_1_3_3_2_5_2","unstructured":"Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai Thomas Unterthiner Mostafa Dehghani Matthias Minderer Georg Heigold Sylvain Gelly et\u00a0al. 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2010.11929 (2020)."},{"key":"e_1_3_3_2_6_2","doi-asserted-by":"crossref","unstructured":"Ren\u00e9e-Pier Filiou M\u00e9lanie Couture Maxime Lussier Aline Aboujaoud\u00e9 Guy Par\u00e9 Sylvain Giroux Hubert Kenfack\u00a0Ngankam Patricia Belchior Carolina Bottari Kevin Bouchard et\u00a0al. 2025. Decision-Making Process of Home and Social Care Professionals Using Telemonitoring of Activities of Daily Living for Risk Assessment: Embedded Mixed Methods Multiple-Case Study. Journal of Medical Internet Research 27 (2025) e64713.","DOI":"10.2196\/64713"},{"key":"e_1_3_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/RadarConf2458775.2024.10548702"},{"key":"e_1_3_3_2_8_2","doi-asserted-by":"crossref","unstructured":"Sha Huan Zhaoyue Wang Xiaoqiang Wang Limei Wu Xiaoxuan Yang Hongming Huang and Gan\u00a0E Dai. 2023. A lightweight hybrid vision transformer network for radar-based human activity recognition. Scientific Reports 13 1 (2023) 17996.","DOI":"10.1038\/s41598-023-45149-5"},{"key":"e_1_3_3_2_9_2","doi-asserted-by":"crossref","unstructured":"Ling Huang Dong Lei Bowen Zheng Guiping Chen Huifeng An and Mingxuan Li. 2024. Lightweight Multi-Domain Fusion Model for Through-Wall Human Activity Recognition Using IR-UWB Radar. Applied Sciences 14 20 (2024) 9522.","DOI":"10.3390\/app14209522"},{"key":"e_1_3_3_2_10_2","doi-asserted-by":"crossref","unstructured":"Irfanullah Khan Antonio Guerrieri Edoardo Serra and Giandomenico Spezzano. 2025. A hybrid deep learning model for UWB radar-based human activity recognition. Internet of Things 29 (2025) 101458.","DOI":"10.1016\/j.iot.2024.101458"},{"key":"e_1_3_3_2_11_2","doi-asserted-by":"crossref","unstructured":"\u015eafak Kili\u00e7 Iman Askerzade and Yilmaz Kaya. 2020. Using ResNet transfer deep learning methods in person identification according to physical actions. IEEE Access 8 (2020) 220364\u2013220373.","DOI":"10.1109\/ACCESS.2020.3040649"},{"key":"e_1_3_3_2_12_2","doi-asserted-by":"crossref","unstructured":"Cong Li Xianpeng Wang Jinmei Shi Han Wang and Liangtian Wan. 2023. Residual neural network driven human activity recognition by exploiting fmcw radar. IEEE Access 11 (2023) 111875\u2013111887.","DOI":"10.1109\/ACCESS.2023.3322726"},{"key":"e_1_3_3_2_13_2","doi-asserted-by":"crossref","unstructured":"Julien Maitre K\u00e9vin Bouchard Camille Bertuglia and S\u00e9bastien Gaboury. 2021. Recognizing activities of daily living from UWB radars and deep learning. Expert Systems with Applications 164 (2021) 113994.","DOI":"10.1016\/j.eswa.2020.113994"},{"key":"e_1_3_3_2_14_2","unstructured":"Yongkun Song Tianxing Yan Ke Zhang Xian Liu Yongpeng Dai and Tian Jin. 2025. A Lightweight Human Activity Recognition Method for Ultra-wideband Radar Based on Spatiotemporal Features of Point Clouds. 5\u00a0pages."},{"key":"e_1_3_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00009"},{"key":"e_1_3_3_2_16_2","doi-asserted-by":"crossref","unstructured":"Zhiwen Xiao and Huagang Tong. 2025. Federated Contrastive Learning With Feature-Based Distillation for Human Activity Recognition. IEEE Transactions on Computational Social Systems (2025).","DOI":"10.1109\/TCSS.2024.3510428"},{"key":"e_1_3_3_2_17_2","doi-asserted-by":"crossref","unstructured":"Linxin Yang and Wenbin Ye. 2024. Design of a Two-Stage Continuous Fall Detection System Using Multiframe Radar Range-Doppler Maps. IEEE Sensors Journal (2024).","DOI":"10.1109\/JSEN.2024.3458068"},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"crossref","unstructured":"Junhao Zhou Chao Sun and Youngok Kim. 2024. Combined Activity Recognition Based on Continuous-wave Radar and Vision Transformer. IEEE Access (2024).","DOI":"10.1109\/ACCESS.2024.3514140"}],"event":{"name":"GoodIT '25: International Conference on Information Technology for Social Good","sponsor":["SIGCAS ACM Special Interest Group on Computers and Society"],"location":"Antwerp Belgium","acronym":"GoodIT '25"},"container-title":["Proceedings of the 2025 International Conference on Information Technology for Social Good"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3748699.3749791","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T10:58:19Z","timestamp":1765450699000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3748699.3749791"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,3]]},"references-count":17,"alternative-id":["10.1145\/3748699.3749791","10.1145\/3748699"],"URL":"https:\/\/doi.org\/10.1145\/3748699.3749791","relation":{},"subject":[],"published":{"date-parts":[[2025,9,3]]},"assertion":[{"value":"2025-12-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}