Ship Detection From Raw SAR Echoes Using Convolutional Neural Networks-Reference-Cited by-同舟云学术

Ship Detection From Raw SAR Echoes Using Convolutional Neural Networks

Published:2024 Issue: Volume:17 Page:9936-9944
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:

De Sousa Kevin¹^ORCID,Pilikos Georgios²,Azcueta Mario³^ORCID,Floury Nicolas²^ORCID

Affiliation:

1. Wave Interaction and Propagation section Radio Frequency Payloads and Technology Division, Electrical Department, European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), Noordwijk, The Netherlands

2. Wave Interaction and Propagation section, Radio Frequency Payloads and Technology Division, Electrical Department, European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), Noordwijk, The Netherlands

3. Copernicus Sentinel-1 Payload section, Copernicus Space Component Space Segment, Earth Observation Projects Department, Directorate of EO Programmes, European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), Noordwijk, The Netherlands

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10526439.pdf?arnumber=10526439

Reference47 articles.

1. Deep Learning Meets SAR: Concepts, Models, Pitfalls, and Perspectives

2. PolSARNet: A Deep Fully Convolutional Network for Polarimetric SAR Image Classification

3. Raw data compression for synthetic aperture radar using deep learning;Pilikos,2022

4. Very deep learning for ship discrimination in Synthetic Aperture Radar imagery

5. Ship-iceberg discrimination with convolutional neural networks in high resolution SAR images;Bentes,2016