A Deformable Spatial Attention Mechanism-Based Method and a Benchmark for Dock Detection-Reference-Cited by-同舟云学术

A Deformable Spatial Attention Mechanism-Based Method and a Benchmark for Dock Detection

Published:2023 Issue: Volume:16 Page:3730-3741
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Tu Yuhong¹^ORCID,Song Yan²^ORCID,Li Beibei¹,Zhu Qiqi¹^ORCID,Cui Songxue³^ORCID,Zhu Haitian³

Affiliation:

1. School of Geography and Information Engineering, China University of Geosciences, Wuhan, China

2. School of Geography and Information Engineering, the School of Public Administration, and the Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences, Wuhan, China

3. National Satellite Ocean Application Service, Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9973430/10097877.pdf?arnumber=10097877

Reference74 articles.

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2. CBAM: Convolutional Block Attention Module

3. Elliptic Fourier transformation-based histograms of oriented gradients for rotationally invariant object detection in remote-sensing images

4. A review on the attention mechanism of deep learning

5. Ship Rotated Bounding Box Space for Ship Extraction From High-Resolution Optical Satellite Images With Complex Backgrounds

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