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Unsupervised Computer Vision for Aerospace Systems : Spacecraft Pose Estimation to Infrastructure Health Monitoring / by Zhaoxiang Zhang.
Springer eBooks EBA - Engineering Collection 2025 Available online
Springer eBooks EBA - Engineering Collection 2025- Format:
- Book
- Author/Creator:
- Zhang, Zhaoxiang.
- Series:
- Scientific Computation, 2198-2589
- Language:
- English
- Subjects (All):
- Computer vision.
- Aerospace engineering.
- Astronautics.
- Machine learning.
- Artificial intelligence.
- Computer Vision.
- Aerospace Technology and Astronautics.
- Machine Learning.
- Artificial Intelligence.
- Local Subjects:
- Computer Vision.
- Aerospace Technology and Astronautics.
- Machine Learning.
- Artificial Intelligence.
- Physical Description:
- 1 online resource (264 pages)
- Edition:
- 1st ed. 2025.
- Place of Publication:
- Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
- Summary:
- This book addresses perception and monitoring challenges in aerospace systems by employing innovative unsupervised learning techniques, thereby providing solutions for scenarios characterized by limited labelled data or dynamic environments. It explores practical methods such as domain adaptation for cross-modal pose estimation, causal inference for point cloud segmentation, and lightweight vision models optimized for edge computing. Key features include algorithm flowcharts, performance comparison tables, and real-world case studies covering planetary crater detection and spacecraft pose estimation. The integration of generative adversarial networks (GANs) for satellite jitter estimation and multistep adaptation strategies for defect detection offers actionable insights, supported by real industrial datasets, embedded hardware schematics, software code snippets, and optimization guidelines for real-time deployment. Engineers and researchers will obtain tools to enhance robustness across modalities and domains, ensuring generalizability in resource-constrained settings. This book serves as a valuable reference for aerospace engineers, computer vision specialists, and remote sensing practitioners and also empowers aerospace infrastructure inspectors adopting advanced vision technologies.
- Contents:
- Introduction
- Jitter Estimation and Compensation in Spacecraft System
- Pose Estimation and Tracking for Space Objects
- Unsupervised Domain Adaptation for Autonomous Perception
- Safety Inspection of Aerospace Infrastructure
- Future Directions.
- Other Format:
- Print version: Zhang, Zhaoxiang Unsupervised Computer Vision for Aerospace Systems
- ISBN:
- 9789819500239
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