eBook
Explainable AI for Earth Observation Data Analysis : Applications, Opportunities, and Challenges
| Title: | Explainable AI for Earth Observation Data Analysis : Applications, Opportunities, and Challenges |
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| Description: | The role of artificial intelligence is crucial in the domain of Earth Observation (EO) data analysis. Deep learning-based approaches have improved accuracy, but they have affected the reliability and transparency of EO data. It is critical to improve the explainability of EO data analysis algorithms and complex deep learning models to ensure the quality of spatial decisions. This book discusses the various advancements in Explainable AI and investigates their suitability for various EO data analyses offering best practices for implementing algorithms that facilitate big and efficient data processing. It lays the foundation of Explainable EO and helps readers build trustworthy, secure, and robust EO systems.Features: Examines explainability of algorithms from the aspect of generalizability and reliability Reviews state-of-the-art explainability strategies related to the preprocessing algorithms Provides explanations for specific evaluation metrics of various EO data processing and preprocessing algorithms Discusses explainable ante-hoc and post-hoc approaches for EO data analysis Serves as a foundational reference for developing future EO data processing strategies Addresses the key challenges in making EO data processing algorithms interpretable and offers insights for the future of explainable EO data processing This book is intended for graduate students, researchers and academics in computer and data science, machine learning, and image processing, as well as professionals in geospatial data science using GIS and remote sensing in Earth and environmental sciences. |
| Authors: | Arun PV, Jocelyn Chanussot, B Krishna Mohan, D Nagesh Kumar, Alok Porwal |
| Resource Type: | eBook. |
| Subjects: | Remote sensing--Data processing, Environmental sciences--Data processing, Artificial intelligence--Environmental applications, Geographic information systems, Geospatial data--Computer processing |
| Categories: | COMPUTERS / Data Science / Machine Learning, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, SCIENCE / Earth Sciences / General, TECHNOLOGY & ENGINEERING / Remote Sensing & Geographic Information Systems |
| Database: | eBook Index |
| ISBN: | 9781032980966 9781003597025 9781040436332 9781040436578 |
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