Machine Learning and Earth Observation for Natural Disasters Management скачать в хорошем качестве

Machine Learning and Earth Observation for Natural Disasters Management

Machine Learning and Earth Observation for Natural Disasters Management 3 June 2025 by Dr. Ioannis Papoutsis National Technical University of Athens, Greece This webinar provided an overview of recent advances in DL techniques for natural hazard applications, and highlighted three core topics. First, the use of spatiotemporal datacubes enables structured representation of geophysical data, facilitating more effective machine learning workflows. Second, Bayesian deep learning and uncertainty quantification techniques enhance model trustworthiness, a crucial requirement for operational disaster response. Finally, emerging AI methodologies, including self-supervised learning and teleconnection-informed forecasting, offer new avenues for improving predictive accuracy and spatio-temporal generalization. Webinar sponsored by IEEE GRSS Remote sensing Environment, Analysis and Climate Technologies (REACT) Technical Committee View the presentation slides: https://acrobat.adobe.com/id/urn:aaid... Learn more: https://www.grss-ieee.org/event/machi...