Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Arindam Sengupta"'
Autor:
Arindam Sengupta
Publikováno v:
International Statistical Review. 91:162-164
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a02396fe521b17e25bf8c42d478b82f4
https://doi.org/10.1111/insr.12538
https://doi.org/10.1111/insr.12538
Publikováno v:
IEEE Sensors Letters. 6:1-4
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cb95f749201adc762666faf50940039
https://doi.org/10.1109/lsens.2022.3213529
https://doi.org/10.1109/lsens.2022.3213529
Publikováno v:
IEEE Robotics and Automation Letters. 7:2875-2882
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a11915aee523867db05f1f223c6d334
https://doi.org/10.1109/lra.2022.3144524
https://doi.org/10.1109/lra.2022.3144524
Autor:
Siyang Cao, Arindam Sengupta
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. :1-12
In this paper we presented mmPose-NLP, a novel Natural Language Processing (NLP) inspired Sequence-to-Sequence (Seq2Seq) skeletal key-point estimator using millimeter-wave (mmWave) radar data. To the best of the author's knowledge, this is the first
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5ec6dc68aa4173f75157cb1e51ad928
https://doi.org/10.1109/tnnls.2022.3151101
https://doi.org/10.1109/tnnls.2022.3151101
Publikováno v:
2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f69675b1261fcb91c043778b78503c46
https://doi.org/10.1109/bhi56158.2022.9926809
https://doi.org/10.1109/bhi56158.2022.9926809
Publikováno v:
Communications in Statistics - Theory and Methods. 51:1179-1196
Asymptotic tests for identical distribution of responses in two independent sets of Likert-type scale data using latent variable models are developed. The proposed tests are compared with regard to...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a421751290cd33d9a4b09635b4eae162
https://doi.org/10.1080/03610926.2021.1872634
https://doi.org/10.1080/03610926.2021.1872634
Publikováno v:
IEEE Sensors Journal. 20:10032-10044
In this paper, mm-Pose, a novel approach to detect and track human skeletons in real-time using an mmWave radar, is proposed. To the best of the authors' knowledge, this is the first method to detect >15 distinct skeletal joints using mmWave radar re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bd9828a409058393a7a26380bcd1000
https://doi.org/10.1109/jsen.2020.2991741
https://doi.org/10.1109/jsen.2020.2991741
Publikováno v:
2020 IEEE Radar Conference (RadarConf20).
In this paper, we review recent and emerging Synthetic Aperture Radar (SAR) applications using mm-Wave radar, ranging from concealed item detection to autonomous systems. Furthermore, relevant machine learning (ML) concepts are introduced and the rev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6881898e5c7dfff5e5ea735e4d467f2d
https://doi.org/10.1109/radarconf2043947.2020.9266501
https://doi.org/10.1109/radarconf2043947.2020.9266501
Publikováno v:
2020 IEEE Radar Conference (RadarConf20).
Human skeletal pose estimation can find several applications ranging from remote patient monitoring, pedestrian detection to defense security and surveillance. However, traditionally used high-resolution vision based sensors suffer operationally duri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cb2dd68464cdf7992d7cb44437cbfcc
https://doi.org/10.1109/radarconf2043947.2020.9266600
https://doi.org/10.1109/radarconf2043947.2020.9266600
In this paper we propose mmFall - a novel fall detection system, which comprises of (i) the emerging millimeter-wave (mmWave) radar sensor to collect the human body's point cloud along with the body centroid, and (ii) a variational recurrent autoenco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91ecf12b8b6d0396064c61fc7f6d5d80
