Deep‐Learning‐Enhanced Electron Microscopy for Earth Material Characterization
Abstract Rocks, as Earth materials, contain intricate microstructures that reveal their geological history. These microstructures include grain boundaries, preferred orientation, twinning and porosity, holding critical significance in the realm of the energy transition. As they influence the physica...
Saved in:
| Main Authors: | Hans vanMelick, Richard Taylor, Oliver Plümper |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-06-01
|
| Series: | Journal of Geophysical Research: Machine Learning and Computation |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2024JH000549 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Advancing cotton fiber research with variable-pressure scanning electron microscopy
by: Fang Bai, et al.
Published: (2025-05-01) -
Palynological Study on Some Grape (Vitis vinifera L.) Cultivars Using Scanning Electron Microscopy
by: Burçak İşçi
Published: (2022-02-01) -
Single Image Signal-to-Noise Ratio (SNR) Estimation Techniques for Scanning Electron Microscope: A Review
by: Dominic Chee Yong Ong, et al.
Published: (2024-01-01) -
Image Generation and Super-Resolution Reconstruction of Synthetic Aperture Radar Images Based on an Improved Single-Image Generative Adversarial Network
by: Xuguang Yang, et al.
Published: (2025-04-01) -
Results of Scanning Electron Microscopy of an Explanted Hydrophilic Acrylic IOL with Hydrophobic Coating
by: G. V. Voronin, et al.
Published: (2023-10-01)