21 citations · 40 across the 20 of their papers we have counts for
5 papers · 1 filter
AI for Extreme Event Modeling and Understanding: Methodologies and Challenges
Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs +22
In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences. Here, AI improved weather forecasting, model emulation, parameter…
Seasonal Fire Prediction using Spatio-Temporal Deep Neural Networks
Dimitrios Michail, Lefki-Ioanna Panagiotou, Charalampos Davalas +4
With climate change expected to exacerbate fire weather conditions, the accurate anticipation of wildfires on a global scale becomes increasingly crucial for disaster mitigation. I…
Causal Graph Neural Networks for Wildfire Danger Prediction
Shan Zhao, Ioannis Prapas, Ilektra Karasante +4
Wildfire forecasting is notoriously hard due to the complex interplay of different factors such as weather conditions, vegetation types and human activities. Deep learning models s…
Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation
Zhitong Xiong, Yi Wang, Fahong Zhang +7
Earth observation (EO) in open-world settings presents a unique challenge: different applications rely on diverse sensor modalities, each with varying ground sampling distances, sp…
Mind the Modality Gap: Towards a Remote Sensing Vision-Language Model via Cross-modal Alignment
Angelos Zavras, Dimitrios Michail, Begüm Demir +1
Deep Learning (DL) is undergoing a paradigm shift with the emergence of foundation models. In this work, we focus on Contrastive Language-Image Pre-training (CLIP), a Vision-Langua…