doppler-vision: A method for personnel recognition using deep convolutional neural networks (DCNNs) based on human micro-Doppler (m-D) signal separation

X. Qiao; T. Shan; R. Tao

doi:10.1049/el.2020.0290

doppler-vision: A method for personnel recognition using deep convolutional neural networks (DCNNs) based on human micro-Doppler (m-D) signal separation

X. Qiao, T. Shan, R. Tao

School of Information and Electronics

Research output: Contribution to journal › Comment/debate

Original language	English
Pages (from-to)	169
Number of pages	1
Journal	Electronics Letters
Volume	56
Issue number	4
DOIs	https://doi.org/10.1049/el.2020.0290
Publication status	Published - 2020

Access to Document

10.1049/el.2020.0290

Cite this

@article{dd29d01e0ee2491ea66ac84d4deed238,

title = "doppler-vision: A method for personnel recognition using deep convolutional neural networks (DCNNs) based on human micro-Doppler (m-D) signal separation",

author = "X. Qiao and T. Shan and R. Tao",

year = "2020",

doi = "10.1049/el.2020.0290",

language = "English",

volume = "56",

pages = "169",

journal = "Electronics Letters",

issn = "0013-5194",

publisher = "John Wiley & Sons Inc.",

number = "4",

}

TY - JOUR

T1 - doppler-vision

T2 - A method for personnel recognition using deep convolutional neural networks (DCNNs) based on human micro-Doppler (m-D) signal separation

AU - Qiao, X.

AU - Shan, T.

AU - Tao, R.

PY - 2020

Y1 - 2020

UR - http://www.scopus.com/inward/record.url?scp=85132979229&partnerID=8YFLogxK

U2 - 10.1049/el.2020.0290

DO - 10.1049/el.2020.0290

M3 - Comment/debate

AN - SCOPUS:85132979229

SN - 0013-5194

VL - 56

SP - 169

JO - Electronics Letters

JF - Electronics Letters

IS - 4

ER -

doppler-vision: A method for personnel recognition using deep convolutional neural networks (DCNNs) based on human micro-Doppler (m-D) signal separation

Access to Document

Other files and links

Cite this