Deep Learning for Multi-Sensor Earth Observation

Section 1: Introduction to Multi-Sensor Data and Artificial Intelligence<br>1. Deep Learning for Multisensor Earth Observation: Introductory Notes<br>2. A Basic Introduction to Deep Learning<br><br>Section 2: Artificial Intelligence for Sensor-specific data analysis and fusion<br>3. Deep learning processing of remotely sensed multispectral images<br>4. Deep Learning and Hyperspectral Images<br>5. Synthetic Aperture Radar Image Analysis in Era of Deep Learning<br>6. Deep Learning with Lidar for Earth Observation<br>7. Several Sensors and Modalities<br><br>Section 3: Advanced Concepts and Architectures<br>8. Self-Supervised Learning for Multimodal Earth Observation Data<br>9. Vision Transformers and Multisensor Earth Observation<br>10. Graph Neural Networks for Multi-Sensor Earth Observation<br>11. Uncertainty Quantification in Deep Neural Networks for Multisensor Earth Observation<br><br>Section 4: Multi-sensor Deep Learning Applications<br>12. Multi-Sensor Deep Learning for Change Detection<br>13. Multi-Sensor Deep Learning for Glacier Mapping<br>14. Deep Learning in Multisensor Agriculture and Crop Management<br>15. Miscellaneous Applications of Deep Learning based Multisensor Earth Observation<br>16. Multi-Sensor Earth Observation: Outlook