Deep neural network maps minerals in petrographic thin sections with high accuracy
A ResNeXt101-UNet deep learning model segments ten mineral phases in petrographic thin sections, reaching a weighted F1-score of 0.863 over ...
A ResNeXt101-UNet deep learning model segments ten mineral phases in petrographic thin sections, reaching a weighted F1-score of 0.863 over ...
One of Europe's oldest geoscience journals is starting a new chapter in its publishing history. The Swiss Journal of Geosciences, ...
A survey of 151 early career geoscientists in Germany finds broad enthusiasm for interdisciplinary research alongside persistent barriers in terminology, ...
A survey of 245 geoscientists shows that parents, especially mothers, are frequently excluded from conferences by childcare, cost, and poor ...
A landmark analysis of nearly 7,000 papers and a survey of 198 cloud physicists reveals deep gender and geographic inequities ...
Researchers at GFZ Potsdam have developed a three-step method that extrapolates a trained neural network's own weight sensitivities to build ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine