Multi-Task Self-Supervised Learning for Vehicle Classification Based on Carrier-Free UWB Radars-Reference-Cited by-同舟云学术

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Multi-Task Self-Supervised Learning for Vehicle Classification Based on Carrier-Free UWB Radars

Published:2022 Issue: Volume:71 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zhu Yuying¹,Chen Si¹^ORCID,Li Xiaoxiong¹^ORCID,Zhang Shuning¹^ORCID,Zhu Lingzhi¹

Affiliation:

1. School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Jiangsu Funding Program for Excellent Postdoctoral Talent

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09849047.pdf?arnumber=9849047

Reference41 articles.

1. A classification-oriented dictionary learning model: Explicitly learning the particularity and commonality across categories

2. An Improved KSVD Algorithm for Ground Target Recognition Using Carrier-Free UWB Radar

3. Hierarchical probabilistic neural network language model;morin;Proc AISTATS,2005

4. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models;gutmann;Proc AISTATS,2010

5. Target Recognition Based on Attributed Scattering Center Models

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