An Efficient and Lightweight CNN Model With Soft Quantification for Ship Detection in SAR Images-Reference-Cited by-同舟云学术

An Efficient and Lightweight CNN Model With Soft Quantification for Ship Detection in SAR Images

Author:

Yang Xi¹^ORCID,Zhang Jianan¹,Chen Chengzeng²,Yang Dong³

Affiliation:

1. State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China

2. Laboratory of Pinghu, Beijing Institute of Infinite Electric Measurement, Pinghu, China

3. Xi’an Institute of Space Radio Technology, Xi’an, China

Funder

National Natural Science Foundation of China

Key Research and Development Program of Shaanxi

Fundamental Research Funds for the Central Universities

Open Research Projects of Laboratory of Pinghu

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference58 articles.

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2. YOLOv3: An incremental improvement;redmon;arXiv 1804 02767,2018

3. Faster R-CNN: Towards real-time object detection with region proposal networks;ren;Proc Adv Neural Inf Process Syst,2015

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