Advances in Machine Learning and Image Analysis for GeoAI presents recent advances in applications and algorithms that are at the intersection of Geospatial imaging and Artificial Intelligence (GeoAI). The book covers algorithmic advances in geospatial image analysis, sensor fusion across modalities, few-shot open-set recognition, explainable AI for Earth Observations, self-supervised learning, image superresolution, Visual Question Answering, and spectral unmixing, among other topics. This book offers a comprehensive resource for graduate students, researchers, and practitioners in the area of geospatial image analysis. It provides detailed descriptions of the latest techniques, best practices, and insights essential for implementing deep learning strategies in GeoAI research and applications.
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1. Introduction 2. Deep Learning for Super-resolution in Remote Sensing 3. Few-Shot Open-Set Recognition of Hyperspectral Images 4. Deep Semantic Segmentation Networks for GeoAI: Impact of Design Choices on Segmentation Performance 5. Estimation of Class Priors for Improving Classification Accuracy 6. Benchmarking and end-to-end considerations for GeoAI-enabled decision making 7. Explainable AI for Earth Observation: Current Methods, Open Challenges, and Opportunities 8. Self-supervised Contrastive Learning for Wildfire Detection: Utility and Limitations 9. Multi-Modal Deep Learning for GeoAI 10. The Power of Voting - Ensemble Learning in Remote Sensing 11. Language and Remote Sensing 12. Spectral Unmixing for Geospatial Image Analysis 13. Applying GeoAI for Effective Large-Scale Wetland Monitoring 14. Leveraging ML approaches for scaling climate data in an atmospheric urban digital twin framework
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A comprehensive overview of the latest techniques and technologies for image analysis and machine learning for geospatial imaging=
Covers the latest machine learning and signal processing techniques that can effectively leverage multimodal geospatial imagery at scale
Chapters cover a variety of algorithmic frameworks pertaining to GeoAI, including superresolution, self-supervised learning, data fusion, explainable AI, among others
Presents cutting-edge deep learning architectures optimized for a wide array of geospatial imagery
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Produktdetaljer
ISBN
9780443190773
Publisert
2024-04-30
Utgiver
Vendor
Elsevier - Health Sciences Division
Vekt
560 gr
Høyde
229 mm
Bredde
152 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
364