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 …
Big Data in Earth system science and progress towards a digital twin
The concept of a digital twin of Earth envisages the convergence of Big Earth Data with
physics-based models in an interactive computational framework that enables monitoring …
physics-based models in an interactive computational framework that enables monitoring …
[Free GPT-4]
Compared with disturbance maps produced at annual or multi-year time steps, monthly
map** of forest harvesting can provide more temporal details needed for studying the …
map** of forest harvesting can provide more temporal details needed for studying the …
[LIVRE][B] What is machine learning?
I El Naqa, MJ Murphy - 2015 - Springer
Abstract Machine learning is an evolving branch of computational algorithms that are
designed to emulate human intelligence by learning from the surrounding environment …
designed to emulate human intelligence by learning from the surrounding environment …
[HTML][HTML] Automated detection of rock glaciers using deep learning and object-based image analysis
Rock glaciers are an important component of the cryosphere and are one of the most visible
manifestations of permafrost. While the significance of rock glacier contribution to streamflow …
manifestations of permafrost. While the significance of rock glacier contribution to streamflow …