Suspicious Object Detection for Millimeter-Wave Images With Multi-View Fusion Siamese Network-Reference-Cited by-同舟云学术

Suspicious Object Detection for Millimeter-Wave Images With Multi-View Fusion Siamese Network

Author:

Guo Dandan¹^ORCID,Tian Long²,Du Chuan³^ORCID,Xie Pengfei⁴^ORCID,Chen Bo⁵^ORCID,Zhang Lei⁴^ORCID

Affiliation:

1. School of Artificial Intelligence, Jilin University, Changchun, China

2. School of Computer Science and Technology, Xidian University, Xi’an, China

3. School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China

4. School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China

5. National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China

Funder

Industry-University-Research Cooperation Fund of the Eighth Research Institute of China Aerospace Science and Technology Corporation

Open Fund of Science and Technology on Electromagnetic Scattering Key Laboratory

Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology

National Natural Science Foundation of China

Shaanxi Youth Innovation Team Project

Fundamental Research Funds for the Central Universities

Shenzhen Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

Reference63 articles.

1. An automatic hybrid approach to detect concealed weopons using deep learning;al-shoukry;ARPN J Eng Appl Sci,2017

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