Deep Learning for Multi-Sensor Earth Observation

Sudipan Saha is currently an Assistant Professor at Yardi School of Artificial Intelligence, Indian Institute of Technology (IIT) Delhi, New Delhi, India. Previously, he worked as a postdoctoral researcher at the Artificial Intelligence for Earth Observation (AI4EO) Lab, Technical University of Munich, Germany (2020-2022). He received a Ph.D. degree in Information and Communication Technologies from the University of Trento and Fondazione Bruno Kessler (FBK), Trento, Italy in 2020, working with Dr. Francesca Bovolo and Prof. Lorenzo Bruzzone. He is the recipient of FBK Best Student Award 2020. Previously, he obtained the M.Tech. degree in Electrical Engineering from IIT Bombay, Mumbai, India in 2014 where he is recipient of Postgraduate Color. He worked as an Engineer with TSMC Limited, Hsinchu, Taiwan, from 2015 to 2016. His research interests are related to multi-temporal and multi-sensor satellite image analysis, uncertainty quantification, deep learning, and climate change.

• Section 1: Introduction to Multi-Sensor Data and Artificial Intelligence1. Deep Learning for Multisensor Earth Observation: Introductory Notes2. A Basic Introduction to Deep LearningSection 2: Artificial Intelligence for Sensor-specific data analysis and fusion3. Deep learning processing of remotely sensed multispectral images4. Deep Learning and Hyperspectral Images5. Synthetic Aperture Radar Image Analysis in Era of Deep Learning6. Deep Learning with Lidar for Earth Observation7. Several Sensors and ModalitiesSection 3: Advanced Concepts and Architectures8. Self-Supervised Learning for Multimodal Earth Observation Data9. Vision Transformers and Multisensor Earth Observation10. Graph Neural Networks for Multi-Sensor Earth Observation11. Uncertainty Quantification in Deep Neural Networks for Multisensor Earth ObservationSection 4: Multi-sensor Deep Learning Applications12. Multi-Sensor Deep Learning for Change Detection13. Multi-Sensor Deep Learning for Glacier Mapping14. Deep Learning in Multisensor Agriculture and Crop Management15. Miscellaneous Applications of Deep Learning based Multisensor Earth Observation16. Multi-Sensor Earth Observation: Outlook