{"id":308,"date":"2025-05-18T15:29:32","date_gmt":"2025-05-18T15:29:32","guid":{"rendered":"https:\/\/research.ece.ncsu.edu\/ci4r\/?page_id=308"},"modified":"2025-07-16T22:27:17","modified_gmt":"2025-07-16T22:27:17","slug":"journal-papers","status":"publish","type":"page","link":"https:\/\/research.ece.ncsu.edu\/ci4r\/journal-papers\/","title":{"rendered":"Journal Papers [33]"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\"><strong>2025<\/strong><\/h3>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"152\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/thms.jpg\" alt=\"\" class=\"wp-image-387 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[33]<\/strong><br><br><strong>Human-Centered Fully-Adaptive Radar for Gesture Recognition in Smart Environments<\/strong><br><em>E. Kurtoglu<\/em> and <em>S.Z. Gurbuz<\/em><br>IEEE Transactions on Human-Machine Systems (THMS)<br><em>In-Production<\/em><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/drive.google.com\/file\/d\/1krVfT9vIhaKgbi6E8_N3LCLkvkof9vUN\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2024<\/strong><\/h3>\n\n\n\n<div style=\"height:24px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"576\" height=\"768\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/GaitPosture.jpg\" alt=\"\" class=\"wp-image-338 size-full\" srcset=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/GaitPosture.jpg 576w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/GaitPosture-225x300.jpg 225w\" sizes=\"auto, (max-width: 576px) 100vw, 576px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[32]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Validation of a Micro-Doppler Radar for Measuring Gait Modifications During Multidirectional Visual Perturbations<\/strong><br>D.M. Martelli, <em>M.M. Rahman<\/em>, and <em>S.Z. Gurbuz<\/em><strong><br><\/strong>Gait and Posture, vol. 113, pp. 504\u2013511, 2024<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0966636224005216\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1DgHg0dLYOW5yZEcmNgjCc_txTOP5oY0d\/view?usp=drive_link\">PDF<\/a> ] <\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"389\" height=\"389\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ojemb.jpg\" alt=\"\" class=\"wp-image-340 size-full\" srcset=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ojemb.jpg 389w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ojemb-300x300.jpg 300w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ojemb-150x150.jpg 150w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ojemb-350x350.jpg 350w\" sizes=\"auto, (max-width: 389px) 100vw, 389px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[31]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Overview of Radar-Based Gait Parameter Estimation Techniques for Fall Risk Assessment<\/strong><br><em>S. Z. Gurbuz, M. M. Rahman<\/em>, Z. Bassiri and D. Martelli<br>IEEE Open Journal of Engineering in Medicine and Biology, vol. 5, pp. 735-749, 2024.<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/10546280\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/14TeAfb7j4bOv8dNF9-qi4FFIkC3Jk_hS\/view?usp=drive_link\">PDF<\/a> ] <\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"196\" height=\"257\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ietrns.jpg\" alt=\"\" class=\"wp-image-344 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[30]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Interactive Learning of Natural Sign Language with Radar<\/strong><br><em>E. Kurtoglu<\/em>, K. DeHaan, C. Kobek Pezzarossi, D.J. Griffin, C. Crawford, <em>S.Z. Gurbuz<\/em><br>IET Radar Sonar and Navigation, 18(8), pp. 1203\u20131216, 2024.<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ietresearch.onlinelibrary.wiley.com\/doi\/10.1049\/rsn2.12565\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1r_jfIhMpWaY-5KJhUnsOfcLhmiTtiMle\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2023<\/strong><\/h3>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"194\" height=\"265\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/trs.jpg\" alt=\"\" class=\"wp-image-349 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[29]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>CV-SincNet: Learning Complex Sinc Filters from Raw Radar Data for Computationally Efficient Human Motion Recognition<\/strong><br>IEEE Transactions on Radar Systems, vol. 1, pp. 493-504, 2023<br>S. Biswas, C. O. Ayna,&nbsp;<em>S.Z. Gurbuz<\/em>, and A.C. Gurbuz<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/10236478\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1qcPqpGNHUfQJtEO-bpjLo-ZeGY2wz7nP\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"194\" height=\"265\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/sensj.jpg\" alt=\"\" class=\"wp-image-350 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[28]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Evaluation of Laser Image Enhancement and Restoration for Underwater Object Recognition<\/strong><br>IEEE Sensors Journal, vol. 23, no. 21, pp. 26136-26153, Nov. 1, 2023<br><em>O. O. Adeoluwa<\/em>, C. D. Moseley, S. M. Kim, P. Kung,&nbsp;<em>S. Z Gurbuz<\/em><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/abstract\/document\/10250195\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1lwcumXJAIUMwpTOl7cyrfYBoC7fRvHM_\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"196\" height=\"257\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ietrns.jpg\" alt=\"\" class=\"wp-image-344 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[27]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Boosting Multi-Target Recognition Performance with MIMO Radar-based Angular Subspace Projection and Multi-View DNN<\/strong><br>IET Radar, Sonar and Navigation, vol. 17, no. 7, July 2023<br><em>E. Kurtoglu<\/em>, S. Biswas, A.C. Gurbuz, and&nbsp;<em>S.Z. Gurbuz<\/em><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ietresearch.onlinelibrary.wiley.com\/doi\/10.1049\/rsn2.12405\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/186vy5CYvejzrkMmmZk0n3cFjMOZ-oHdl\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"194\" height=\"265\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/sensj.jpg\" alt=\"\" class=\"wp-image-350 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[26]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Sensing and Machine Learning for Automotive Perception: A Review<br><\/strong>IEEE Sensors Journal, vol. 23, iss. 11, June 2023&nbsp;<br>A. Pandharipande, C.-H. Cheng, J. Dauwels,&nbsp;<em>S. Z. Gurbuz<\/em>, J. Ibanex-Guzman, G. Li, A. Piazzoni, P. Wang, A. Santra<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/10089400\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/195aVQ3v3j8D70DWLtxKY7g8TzGb992eg\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[25]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Physics-Aware Generative Adversarial Network for Human Activity Recognition<\/strong><br>IEEE Transactions on Aerospace and Electronic Systems, vol. 59, no. 3, pp. 2994-3008, June 2023.<br><em>M.M. Rahman,&nbsp;S.Z. Gurbuz<\/em>, and M.G. Amin<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/9944857\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1_xcepcqRNMgP2wpEbkV9JRKCbVHKHdnQ\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2022<\/strong><\/h3>\n\n\n\n<div style=\"height:23px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"192\" height=\"262\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/smarthealth.jpg\" alt=\"\" class=\"wp-image-378 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[24]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Gait Variability Analysis using Continuous RF Data Streams of&nbsp;Human Activity&nbsp;<\/strong><br>Elsevier Smart Health Journal, Vol. 26, Oct. 2023&nbsp;<br>Special Issue for IEEE\/ACM&nbsp;Int. Conf. on Connected Health: Applications, Systems&nbsp;and Engineering Technologies (CHASE)<br><em>S.Z Gurbuz, E. Kurtoglu, M.M. Rahman<\/em>, and D. Martelli<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S235264832200068X\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1b7TrTX2DO_1PwqL2aupMT43PKVN7bnXo\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[23]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Effect of Kinematics and Fluency in Adversarial Synthetic Data Generation for ASL Recognition with RF Sensors<\/strong><br>IEEE Transactions on Aerospace and Electronic Systems,&nbsp;Volume: 58, Iss. 4, August 2022&nbsp;<br><em>M.M. Rahman<\/em>, E.A. Malaia, A.C. Gurbuz, D. Griffin, C. Crawford and&nbsp;<em>S.Z. Gurbuz<\/em><br>*&nbsp;<a href=\"https:\/\/arxiv.org\/abs\/2201.00055\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/arxiv.org\/abs\/2201.00055<\/a>&nbsp;(Jan 2022)<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/9669011\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1eHOySbuVkdFPPaRMlCOscu83QJjoE-V_\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"152\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/thms.jpg\" alt=\"\" class=\"wp-image-387 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[22]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>ASL Trigger Recognition in Mixed Activity\/Signing Sequences for RF Sensor-Based User Interfaces<\/strong><br>IEEE Transactions on Human Machine Systems,&nbsp;Volume: 52, Iss. 4, August 2022<br><em>E. Kurtoglu<\/em>, A.C. Gurbuz, E.A. Malaia, D. Griffin, C. Crawford, and<strong>&nbsp;<\/strong><em>S.Z. Gurbuz<\/em><br>*&nbsp;<a href=\"https:\/\/arxiv.org\/abs\/2111.05480\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/arxiv.org\/abs\/2111.05480<\/a>&nbsp;(Dec. 2021)<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/9660776\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1AQ24smo1dEm-BzxWcGobx-XHgIKV8WN7\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"189\" height=\"267\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/linguisticsvanguard.jpg\" alt=\"\" class=\"wp-image-389 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[21]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Complexity in Sign languages: Linguistic and Dimensional Analysis of Information Transfer in Dynamic Visual Communication&nbsp;<br><\/strong>Linguistic Vanguard, vol. 9, no. s1, 2023, pp. 121-131, published online in October 2022.<br>E.A. Malaia, J.D. Borneman,&nbsp;<em>E. Kurtoglu,&nbsp;S.Z. Gurbuz<\/em>, D. Griffin, C. Crawford, and A.C. Gurbuz<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/lingvan-2021-0005\/html\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1SXacm5KTE8luy85D0dXB3F4cIHkrr0iO\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"194\" height=\"265\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/sensj.jpg\" alt=\"\" class=\"wp-image-350 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[20]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Multi-Frequency RF Sensor Fusion for Word-Level Fluent ASL Recognition&nbsp;<\/strong><br>IEEE Sensors Journal,&nbsp;Volume: 22, Iss. 12, pp. 11373-11381, June 2022<br><em>S.Z. Gurbuz,&nbsp;M.M. Rahman, E. Kurtoglu<\/em>, E. Malaia, A.C. Gurbuz, D.J. Griffin, C. Crawford<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/9425571\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1uyr6imD1eeT6sACNN84Plnwp2AVhPG-k\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2021<\/strong><\/h3>\n\n\n\n<div style=\"height:26px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"194\" height=\"265\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/sensj.jpg\" alt=\"\" class=\"wp-image-350 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[19]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Sequential Human Gait Classification with Distributed Radar Sensor Fusion<\/strong>&nbsp;&nbsp;<br>IEEE Sensors Journal, vol. 21, iss. 6, March 2021<br>H. Li, A. Mehul, J. Le Kernec,&nbsp;<em>S.Z. Gurbuz<\/em>, F. Fioranelli<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/9306810\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/12fBq55Awh2Ga5ehkIK9um0S1A9mhMUVY\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"194\" height=\"265\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/sensj.jpg\" alt=\"\" class=\"wp-image-350 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[18]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>American Sign Language Recognition Using RF Sensing&nbsp;<br><\/strong>IEEE Sensors Journal, vol. 21, iss. 3, Feb. 2021<br>* IEEE Early Access, September 7, 2020<br><em>S.Z. Gurbuz<\/em>, A.C. Gurbuz, E. Malaia, D. Griffin, C. Crawford,&nbsp;<em>M. Rahman, E. Kurtoglu, R. Aksu, T. Macks<\/em><strong>,<\/strong>&nbsp;R. Mdrafi<br>*&nbsp;<a href=\"https:\/\/arxiv.org\/abs\/2009.01224\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/arxiv.org\/abs\/2009.01224<\/a>&nbsp; (August 2020)<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/9187644\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1jC-PDC0eEJK83mWZzio8rpr4aY-ItGJM\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2020<\/strong><\/h3>\n\n\n\n<div style=\"height:24px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[17]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Motion classification using kinematically sifted ACGAN-synthesized radar micro-Doppler signatures&nbsp;<\/strong><br>IEEE Transactions on Aerospace and Electronic Systems, Vol. 56, Iss. 4, pp.&nbsp;3197&nbsp;&#8211; 3213, August 2020<br>B Erol,&nbsp;<em>S.Z. Gurbuz<\/em>, and M.G. Amin<br>* IEEExplore Early Access: January 27, 2020<br>*&nbsp;<a href=\"https:\/\/arxiv.org\/abs\/2001.08582\">https:\/\/arxiv.org\/abs\/2001.08582<\/a>&nbsp;(January 2020)<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/8970277\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1SfymtTeUynjIsqJE91UnfVS_f_J9qMdn\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2019<\/strong><\/h3>\n\n\n\n<div style=\"height:22px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile is-vertically-aligned-top\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"194\" height=\"265\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/maes_2019.jpg\" alt=\"\" class=\"wp-image-398 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[16]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>An overview of cognitive radar: past, present, and future*&nbsp;<br><\/strong>IEEE Aerospace and Electronic Systems Magazine, Vol. 34, Iss. 12, pp. 6 &#8211; 18, Dec. 2019<br><strong>S.Z. Gurbuz<\/strong>, H. Griffiths, A. Charlish, M. Rangaswamy, M.S. Greco, and K. Bell<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/8961364\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1ZMf4fuePflXNhbzfZdHcc6CRm-xZdhVc\/view?usp=drive_link\">PDF<\/a> ] <\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">* Paper recognized with 2019 IEEE Harry Rowe Mimno Award [ <a href=\"https:\/\/ieee-aess.org\/awards\/harry-rowe-mimno-award#recipients\">AESS Link<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"586\" height=\"800\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/spmcover_1.png\" alt=\"\" class=\"wp-image-400 size-full\" srcset=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/spmcover_1.png 586w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/spmcover_1-220x300.png 220w\" sizes=\"auto, (max-width: 586px) 100vw, 586px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[15]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Radar-based human motion recognition with deep learning&nbsp;<\/strong><br>IEEE Signal Processing Magazine, Vol. 36, Iss. 4, pp. 16 &#8211; 28, July 2019<br>Special Issue on Advances in Radar Systems for Modern Civilian and Commercial Applications<br><em>S.Z. Gurbuz,<\/em><strong>&nbsp;<\/strong>M.G. Amin<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/8746862\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1bHY6DrGshvXRTCGoYB_3ov6gxXyq9LId\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[14]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>DNN transfer learning from diversified micro-Doppler for motion classification<\/strong>&nbsp;<br>IEEE Transactions on Aerospace and Electronic Systems,&nbsp;vol. 55, no. 5, pp. 2164 &#8211; 2180, Oct. 2019<br>B. Erol,&nbsp;<em>S.Z. Gurbuz<\/em>, M.G. Amin<br>*&nbsp;<a href=\"https:\/\/arxiv.org\/abs\/1811.08361v1\">https:\/\/arxiv.org\/abs\/1811.08361v1<\/a>&nbsp;(November 2018)<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/8572732\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1p2x7WqDhi3uA-TNae0jqrBCN7_AVvfQu\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2018<\/strong><\/h3>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[13]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities<\/strong><br>IEEE Transactions on Aerospace and Electronic Systems, vol. 54, iss. 4, pp. 1709 &#8211; 1723, August 2018<br><em>M.S. Seyfioglu<\/em>, A.M. Ozbayoglu,&nbsp;<em>S.Z. Gurbuz<\/em><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/8283539\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1MN1DwOU6Xb4h1yYPLfLip7BxoWknP6s2\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[12]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Automatic data-driven frequency-warped cepstral feature design for micro-Doppler classification<\/strong><br>IEEE Transactions on Aerospace and Electronic Systems, vol. 54, iss. 4, pp. 1724 &#8211; 1738, August 2018<br>B. Erol,&nbsp;<em>S.Z. Gurbuz<\/em>, and M.G. Amin<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/8279431\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1-AAvH2AzctaxCZRZWq2ER80K_Ay6l85a\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2017<\/strong><\/h3>\n\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"618\" height=\"800\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig.png\" alt=\"\" class=\"wp-image-423 size-full\" srcset=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig.png 618w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig-232x300.png 232w\" sizes=\"auto, (max-width: 618px) 100vw, 618px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[11]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Deep neural network initialization methods for micro-Doppler classification with low training sample support&nbsp;<\/strong><br>IEEE Geoscience and Remote Sensing Letters, Vol. 14, No. 12, pp.&nbsp;2462-2466, Dec. 2017<br>M.S. Seyfioglu,&nbsp;<em>S.Z. Gurbuz<\/em><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/8119733\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1z9IEcTFKsts5mV5W8kad7KCDuwEshKWD\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[10]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Feature Diversity for Optimized Human Micro-Doppler Classification Using Multistatic Radar<\/strong><br>IEEE Transactions of Aerospace and Electronic Systems, Vol. 53, No. 2, pp. 640-654, April 2017<br>F. Fioranelli, M. Ritchie,&nbsp;<em>S.Z. Gurbuz<\/em>, H. Griffiths<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/7814264\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1NfacDbHq7jqyZuBLZyRQOKp6-5LjO9Jz\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"196\" height=\"257\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ietrns.jpg\" alt=\"\" class=\"wp-image-344 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[9]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Micro-Doppler Based In-Home Aided and Unaided Walking Recognition with Multiple Radar and Sonar Systems<\/strong><br>IET Radar, Sonar and Navigation, Vol. 11, No. 1, pp. 107-115, April 2017<br><em>S.Z. Gurbuz<\/em>, C. Clemente, A. Balleri, J. Soraghan<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ietresearch.onlinelibrary.wiley.com\/doi\/abs\/10.1049\/iet-rsn.2016.0055\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1HYb-Hz0UFlOLCb2UsOe5Ca8luqvM2M3J\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2016<\/strong><\/h3>\n\n\n\n<div style=\"height:27px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:16% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"618\" height=\"800\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/tgrs-cover-2017-vol55-iss5_orig.png\" alt=\"\" class=\"wp-image-426 size-full\" srcset=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/tgrs-cover-2017-vol55-iss5_orig.png 618w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/tgrs-cover-2017-vol55-iss5_orig-232x300.png 232w\" sizes=\"auto, (max-width: 618px) 100vw, 618px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[8]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Information Theoretic Feature Selection for Human Micro-Doppler Signature Classification&nbsp;<\/strong><br>IEEE Transactions on Geoscience and Remote Sensing, Vol. 55, No. 5, pp. 2749-2762, May 2016&nbsp;<br>B. Tekeli,&nbsp;<em>S.Z. Gurbuz<\/em>, M. Yuksel<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/7374670\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/11tv1MZOAmg4EKro1eowD7UmQDXYuJVh8\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2015<\/strong><\/h3>\n\n\n\n<div style=\"height:28px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"196\" height=\"257\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ietrns.jpg\" alt=\"\" class=\"wp-image-344 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[<\/strong>7]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Operational Assessment and Adaptive Selection of Micro-Doppler Features<\/strong><br>IET Radar, Sonar, and Navigation, Vol. 9, No. 9, pp. 1196-1204, Dec. 2015<br><em>S.Z. Gurbuz<\/em>, B. Erol, B. Cagliyan, B. Tekeli<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ietresearch.onlinelibrary.wiley.com\/doi\/abs\/10.1049\/iet-rsn.2015.0144\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/14pZPrXhd32-8bNVnUeFDCHz8r0Ht8D_X\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"618\" height=\"800\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig.png\" alt=\"\" class=\"wp-image-423 size-full\" srcset=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig.png 618w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig-232x300.png 232w\" sizes=\"auto, (max-width: 618px) 100vw, 618px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[6]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Knowledge Exploitation for Human Micro-Doppler Classification&nbsp;<\/strong><br>IEEE Geoscience and Remote Sensing Letters, Vol. 12, No. 10, pp. 2125-2129, October 2015<br>C. Karabacak,&nbsp;<em>S.Z. G\u00fcrb\u00fcz<\/em>, A.C. G\u00fcrb\u00fcz, M.B. Guldogan, G. Hendeby, F. Gustafsson<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/7165625\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/180j2PbP05nFOYHQ4oZjFcnKOZPB0d2U2\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"618\" height=\"800\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig.png\" alt=\"\" class=\"wp-image-423 size-full\" srcset=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig.png 618w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/gsrlcover_orig-232x300.png 232w\" sizes=\"auto, (max-width: 618px) 100vw, 618px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[5]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Human Activity Classification Using the Wireless, Mote-Scale Bumblebee Radar&nbsp;<\/strong><br>IEEE Geoscience and Remote Sensing Letters, Vol. 12, No. 10, pp. 2135-2139, October 2015<br>B. \u00c7a\u011fl\u0131yan,&nbsp;<em>S.Z. G\u00fcrb\u00fcz<\/em><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/7172472\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1EzYr41VvDwgIItQ0hxaY6I0UuxrhO9pQ\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"189\" height=\"267\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/ieice_cover.png\" alt=\"\" class=\"wp-image-430 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong><strong>[4]<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Implementation of an Enhanced Target Localization and Identification Algorithm on a Magnetic WSN<\/strong><br>IEICE Transactions on Communications, Vol. E98-B, No. 10, pp. 2022-2023, October 2015<br>S. Baghaee,&nbsp;<em>S.Z. G\u00fcrb\u00fcz<\/em>, E. Uysal-B\u0131y\u0131ko\u011flu<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/globals.ieice.org\/en_transactions\/communications\/10.1587\/transcom.E98.B.2022\/_p\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1jhpaTKOYYq2-w1QXn9rN2Ab9NSs69n_h\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<div style=\"height:17px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><a href=\"https:\/\/drive.google.com\/file\/d\/1IONtXe2OgJCXLLIK9CHnNhLRMW-P5Yxf\/view?usp=drive_link\"><img loading=\"lazy\" decoding=\"async\" width=\"392\" height=\"477\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/alperenmaes_orig.jpg\" alt=\"\" class=\"wp-image-431 size-full\" srcset=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/alperenmaes_orig.jpg 392w, https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/alperenmaes_orig-247x300.jpg 247w\" sizes=\"auto, (max-width: 392px) 100vw, 392px\" \/><\/a><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[3]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>A Kinect-Based Human Micro-Doppler Simulator<\/strong>*<br>IEEE Aerospace and Systems Magazine, Vol. 30, No. 5, May 2015<br>B.Erol, C. Karabacak,&nbsp;<em>S.Z. G\u00fcrb\u00fcz<\/em><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/7119820\">Link to Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1P3dkqoeJtSDFNa-q4VlGZfXM-CSszvcR\/view?usp=drive_link\">PDF<\/a> ]\n\n\n\n<p class=\"has-slightly-smaller-font-size\">*Kid on the cover is my son <a href=\"https:\/\/www.linkedin.com\/in\/mustafa-alperen-gurbuz-64b996248\/\">Mustafa Alperen Gurbuz<\/a> \ud83d\ude42<\/p>\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2012<\/strong><\/h3>\n\n\n\n<div style=\"height:23px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[2]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>Kinematic Model-Based Human Detectors for Multi-Channel Radar&nbsp;<\/strong><br>IEEE Transactions on Aerospace and Electronic Systems, Vol. 48, No. 2, pp. 1306-1318, April 2012<br><em>S.Z. G\u00fcrb\u00fcz<\/em>, W.L. Melvin, D.B. Williams.<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/6178063\">Link to the Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/1SO-4Bp3sjLCOQ9ygJ0B7QrBw4MVLgo-D\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2011<\/strong><\/h3>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"110\" height=\"146\" src=\"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-content\/uploads\/sites\/40\/2025\/05\/taes.gif\" alt=\"\" class=\"wp-image-375 size-full\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"has-slightly-smaller-font-size\"><strong>[1]<\/strong><\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\"><strong>A Non-Linear Phase, Model-Based Human Detector for Radar<\/strong><br>IEEE Transactions in Aerospace and Electronic Systems, Vol. 47, No. 4, pp. 1306-1318, October 2011<br><em>S.Z. G\u00fcrb\u00fcz<\/em>, W.L. Melvin, and D.B. Williams<\/p>\n\n\n\n<p class=\"has-slightly-smaller-font-size\">[ <a href=\"https:\/\/ieeexplore.ieee.org\/document\/6034647\">Link to the Pub<\/a> ] [ <a href=\"https:\/\/drive.google.com\/file\/d\/13Wk_EAXHE0KMN1OlyTvDQZGjo43yjyD0\/view?usp=drive_link\">PDF<\/a> ]\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>2025 [33] Human-Centered Fully-Adaptive Radar for Gesture Recognition in Smart EnvironmentsE. Kurtoglu and S.Z. GurbuzIEEE Transactions on Human-Machine Systems (THMS)In-Production [ PDF ] 2024 [32]&#8230;<\/p>\n","protected":false},"author":149,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-308","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-json\/wp\/v2\/pages\/308","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-json\/wp\/v2\/users\/149"}],"replies":[{"embeddable":true,"href":"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-json\/wp\/v2\/comments?post=308"}],"version-history":[{"count":66,"href":"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-json\/wp\/v2\/pages\/308\/revisions"}],"predecessor-version":[{"id":1104,"href":"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-json\/wp\/v2\/pages\/308\/revisions\/1104"}],"wp:attachment":[{"href":"https:\/\/research.ece.ncsu.edu\/ci4r\/wp-json\/wp\/v2\/media?parent=308"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}