{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T15:32:05Z","timestamp":1770046325338,"version":"3.49.0"},"reference-count":10,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,4,12]]},"abstract":"<jats:p>This paper proposes a Wi-Fi-based indoor human detection system using a deep convolutional neural network. The system detects different human states in various situations, including different environments and propagation paths. The main improvements proposed by the system is that there is no cameras overhead and no sensors are mounted. This system captures useful amplitude information from the channel state information and converts this information into an image-like two-dimensional matrix. Next, the two-dimensional matrix is used as an input to a deep convolutional neural network (CNN) to distinguish human states. In this work, a deep residual network (ResNet) architecture is used to perform human state classification with hierarchical topological feature extraction. Several combinations of datasets for different environments and propagation paths are used in this study. ResNet\u2019s powerful inference simplifies feature extraction and improves the accuracy of human state classification. The experimental results show that the fine-tuned ResNet-18 model has good performance in indoor human detection, including people not present, people still, and people moving. Compared with traditional machine learning using handcrafted features, this method is simple and effective.<\/jats:p>","DOI":"10.3233\/jifs-189629","type":"journal-article","created":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T18:34:30Z","timestamp":1610476470000},"page":"8063-8072","source":"Crossref","is-referenced-by-count":0,"title":["Deep convolutional neural networks for human movement detection using wireless signals"],"prefix":"10.1177","volume":"40","author":[{"given":"Chien-Cheng","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan"}]},{"given":"Zhongjian","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan"},{"name":"School of Mechanical and Electrical Engineering, Sanming University, Fujian, China"}]},{"given":"Xiu-Chi","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-189629_ref2","doi-asserted-by":"crossref","first-page":"64323","DOI":"10.1109\/ACCESS.2019.2917620","article-title":"Diversity in Machine Learning","volume":"7","author":"Gong","year":"2019","journal-title":"IEEE Access"},{"issue":"6","key":"10.3233\/JIFS-189629_ref7","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1007\/s00779-009-0277-9","article-title":"#246, se, An activity monitoring system for elderly care using generative and discriminative models","volume":"14","author":"Kasteren","year":"2010","journal-title":"Personal Ubiquitous Comput"},{"issue":"4","key":"10.3233\/JIFS-189629_ref12","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1007\/s11554-012-0246-9","article-title":"Fall detection system using Kinect\u2019s infrared sensor","volume":"9","author":"Mastorakis","year":"2014","journal-title":"J Real-Time Image Process"},{"issue":"24","key":"10.3233\/JIFS-189629_ref13","doi-asserted-by":"crossref","first-page":"9468","DOI":"10.1016\/j.eswa.2015.07.076","article-title":"Addressing imbalanced data with argument based rule learning","volume":"42","author":"Napiera\u0142a","year":"2015","journal-title":"Expert Systems with Applications"},{"issue":"6","key":"10.3233\/JIFS-189629_ref15","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1007\/s00779-012-0552-z","article-title":"Introducing the use of depth data for fall detection","volume":"17","author":"Planinc","year":"2013","journal-title":"Personal Ubiquitous Comput"},{"issue":"7","key":"10.3233\/JIFS-189629_ref20","doi-asserted-by":"crossref","first-page":"17195","DOI":"10.3390\/s150717195","article-title":"Robust indoor human activity recognition using wireless signals","volume":"15","author":"Wang","year":"2015","journal-title":"Sensors"},{"issue":"5","key":"10.3233\/JIFS-189629_ref22","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1109\/TMC.2009.174","article-title":"Radio Tomographic Imaging with Wireless Networks","volume":"9","author":"Wilson","year":"2010","journal-title":"IEEE Transactions on Mobile Computing"},{"issue":"11","key":"10.3233\/JIFS-189629_ref23","doi-asserted-by":"crossref","first-page":"2329","DOI":"10.1109\/JSAC.2015.2430294","article-title":"Non-Invasive Detection of Moving and Stationary Human With WiFi","volume":"33","author":"Wu","year":"2015","journal-title":"IEEE Journal on Selected Areas in Communications"},{"issue":"2","key":"10.3233\/JIFS-189629_ref26","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1007\/s11390-011-9430-9","article-title":"Activity recognition based on RFID object usage for smart mobile devices","volume":"26","author":"Yang","year":"2011","journal-title":"J Comput Sci Technol"},{"issue":"2","key":"10.3233\/JIFS-189629_ref27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2543581.2543592","article-title":"From RSSI to CSI: Indoor localization via channel response","volume":"46","author":"Yang","year":"2013","journal-title":"ACM Comput Surv"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-189629","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T04:29:29Z","timestamp":1770006569000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-189629"}},"subtitle":[],"editor":[{"given":"Wen-Hsiang","family":"Hsieh","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,4,12]]},"references-count":10,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/jifs-189629","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,12]]}}}