Synthetic aperture radar (SAR) meets deep learning / Tianwen Zhang, Tianjiao Zeng, Xiaoling Zhang, editor.

Format:

Book

Contributor:

Zhang, Xiaoling, editor.

Zeng, Tianjiao, editor.

Zhang, Tianwen, editor.

Language:

English

Subjects (All):

Marine pollution.

Physical Description:

1 online resource (386 pages)

Other Title:

Synthetic Aperture Radar

Place of Publication:

[Basel] : MDPI - Multidisciplinary Digital Publishing Institute, 2023.

Language Note:

In English.

Summary:

This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports.

Contents:

Introduction

Overview of Contribution

Conclusions

Author Contributions

Data Availability Statement

Acknowledgments

Conflicts of Interest

References.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

3-0365-6383-0