@inproceedings{68a75ca1f4bd406582a981c569268d9c,
title = "An Unsupervised Domain Adaptation-Based Device-Free Sensing Approach for Cross-Weather Target Recognition in Foliage Environments",
abstract = "In recent years, the emerging technique of device-free sensing (DFS) has gained popularity for foliage penetration (FOPEN) target recognition. This popularity is primarily attributed to its inherent advantage of not requiring specialized sensing equipment beyond wireless transceivers. Concerning weather variations, DFS heavily relies on labeled data for model training, which necessitates the annotation of samples for each weather environment. However, this annotation process proves impractical for real-world applications, especially under adverse weather conditions. To address this issue, this paper presents an unsupervised domain adaptation (UDA)-based cross-weather FOPEN target recognition system (CW-FTRS). Experimental results validate that the proposed method achieves an average accuracy of over 72% in unseen weather conditions using only unlabeled data samples.",
keywords = "Device-free sensing, Foliage penetration, Target recognition, Unsupervised domain adaptation",
author = "Yi Zhong and Tianqi Bi and Ju Wang and Minglei You and Ting Jiang",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; International Conference on Communications, Signal Processing, and Systems, CSPS 2023 ; Conference date: 22-07-2023 Through 23-07-2023",
year = "2024",
doi = "10.1007/978-981-99-7502-0_18",
language = "English",
isbn = "9789819975556",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "167--175",
editor = "Wei Wang and Xin Liu and Zhenyu Na and Baoju Zhang",
booktitle = "Communications, Signal Processing, and Systems - Proceedings of the 12th International Conference on Communications, Signal Processing, and Systems",
address = "Germany",
}