Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Sevgi Zubeyde Gurbuz"'
Autor:
Shelly Vishwakarma, Kevin Chetty, Julien Le Kernec, Qingchao Chen, Raviraj Adve, Sevgi Zubeyde Gurbuz, Wenda Li, Shobha Sundar Ram, Francesco Fioranelli
Publikováno v:
IET Radar, Sonar & Navigation, Vol 18, Iss 2, Pp 235-238 (2024)
Externí odkaz:
https://doaj.org/article/f8a87bdd79684e1c8beff9ce78432ffd
Publikováno v:
IET Radar, Sonar & Navigation, Vol 17, Iss 7, Pp 1115-1128 (2023)
Abstract Current radio frequency (RF) classification techniques assume only one target in the field of view. Multi‐target recognition is challenging because conventional radar signal processing results in the superposition of target micro‐Doppler
Externí odkaz:
https://doaj.org/article/eecf85c217fc4987ac397e00d6418fda
Autor:
Mohammad Mahbubur Rahman, Evie A. Malaia, Ali Cafer Gurbuz, Darrin J. Griffin, Chris Crawford, Sevgi Zubeyde Gurbuz
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems. 58:2732-2745
RF sensors have been recently proposed as a new modality for sign language processing technology. They are non-contact, effective in the dark, and acquire a direct measurement of signing kinematic via exploitation of the micro-Doppler effect. First,
Autor:
Ali Cafer Gurbuz, Evie Malaia, Emre Kurtoglu, Darrin J. Griffin, Chris S. Crawford, M. Mahbubur Rahman, Sevgi Zubeyde Gurbuz
Publikováno v:
IEEE Sensors Journal. 22:11373-11381
Deaf spaces are unique indoor environments designed to optimize visual communication and Deaf cultural expression. However, much of the technological research geared towards the deaf involve use of video or wearables for American sign language (ASL)
Autor:
Avik Santra, Ashish Pandharipande, Pu Perry Wang, Sevgi Zubeyde Gurbuz, Javier Ibanez-Guzman, Chih-Hong Cheng, Justin Dauwels, Guofa Li
Publikováno v:
IEEE Sensors Journal. 23:11116-11116
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems. 56:3197-3213
Deep neural networks have recently received a great deal of attention in applications requiring classification of radar returns, including radar-based human activity recognition for security, smart homes, assisted living, and biomedicine. However, ac
Autor:
Chris S. Crawford, Emre Kurtoglu, Darrin J. Griffin, Ali Cafer Gurbuz, Evie Malaia, Sevgi Zubeyde Gurbuz, Robiulhossain Mdrafi, M. Mahbubur Rahman
Publikováno v:
ICASSP
Current research in the recognition of American Sign Language (ASL) has focused on perception using video or wearable gloves. However, deaf ASL users have expressed concern about the invasion of privacy with video, as well as the interference with da
Autor:
Moeness G. Amin, Sevgi Zubeyde Gurbuz
Publikováno v:
IEEE Signal Processing Magazine. 36:16-28
Deep learning (DL) has shown tremendous promise in radar applications that involve target classification and imaging. In the field of indoor monitoring, researchers have shown an interest in DL for classifying daily human activities, detecting falls,
Publikováno v:
2021 IEEE Radar Conference (RadarConf21).
The widespread availability of low-cost RF sensors has made it easier to construct RF sensor networks for motion recognition, as well as increased the availability of RF data across a variety of frequencies, waveforms, and transmit parameters. Howeve
Publikováno v:
2021 IEEE Radar Conference (RadarConf21).
Generative adversarial networks (GANs) have been recently proposed for the synthesis of RF micro-Doppler signatures to mitigate the problem of low sample support and enable the training of deeper neural networks (DNNs) for improved RF signal classifi