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Artificial intelligence for geoscience: Progress, challenges and perspectives
This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …
traditional physics-based models to modern data-driven approaches facilitated by significant …
Deep learning and artificial intelligence in sustainability: a review of SDGs, renewable energy, and environmental health
Artificial intelligence (AI) and deep learning (DL) have shown tremendous potential in
driving sustainability across various sectors. This paper reviews recent advancements in AI …
driving sustainability across various sectors. This paper reviews recent advancements in AI …
A prolonged artificial nighttime-light dataset of China (1984-2020)
Nighttime light remote sensing has been an increasingly important proxy for human
activities. Despite an urgent need for long-term products and pilot explorations in …
activities. Despite an urgent need for long-term products and pilot explorations in …
Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery
Unsupervised pre-training methods for large vision models have shown to enhance
performance on downstream supervised tasks. Develo** similar techniques for satellite …
performance on downstream supervised tasks. Develo** similar techniques for satellite …
Fine-tuning can distort pretrained features and underperform out-of-distribution
A Kumar, A Raghunathan, R Jones, T Ma… - ar** achieve Sustainable
Development Goals and tackle climate change, has not yet benefited from the recent …
Development Goals and tackle climate change, has not yet benefited from the recent …