CTF-Net: A Convolutional and Transformer Fusion Network for SAR Ship Detection-Reference-Cited by-同舟云学术

CTF-Net: A Convolutional and Transformer Fusion Network for SAR Ship Detection

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Wu Haoyu¹^ORCID,Yu Lei²^ORCID,Li Xiangwen¹,Zhou Lin¹,Zhang Wenjing¹,Bai Guiming¹

Affiliation:

1. Department of Electronic Information and Computer Engineering, The Engineering and Technology College of Chengdu University of Technology, Leshan, China

2. School of Information and Communication Engineering, Harbin Engineering University, Harbin, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10234414.pdf?arnumber=10234414

Reference24 articles.

1. FCOS: Fully Convolutional One-Stage Object Detection

2. Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

3. An Anchor-Free Detection Method for Ship Targets in High-Resolution SAR Images

4. SSD: Single shot MultiBox detector;liu;Proc Eur Conf Comput Vis,2016

5. Remote Sensing Image Change Detection With Transformers

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