Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025 ...

Graph neural networks (GNNs) have rapidly emerged as a central methodology for analysing complex datasets presented as graphs, where entities are interconnected through diverse relationships. By ...

The transformer-based semantic segmentation approaches, which divide the image into different regions by sliding windows and model the relation inside each window, have achieved outstanding success.

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...