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CAGEY (CArbonate Grain Estimation with YOLO): Object detection for grain size, roundness, and dunham classification

Accurate grain size and roundness analysis is crucial for geological applications such as paleoenvironmental reconstructions or reservoir characterization, but traditional manual methods are time-consuming and prone to error. In this study, we introduce the CAGEY (CArbonate Grain Estimation with YOL...

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Hauptverfasser: Bingxuan Liu, Haifa AlSalmi, Cédric M. John
Format: Artigo
Sprache:Inglês
Veröffentlicht: Elsevier 2026-02-01
Schriftenreihe:Applied Computing and Geosciences
Schlagworte:
Carbonate grain
Object detection
YOLOv5s
Lithology classification
Core images
Deep learning
Online-Zugang:http://www.sciencedirect.com/science/article/pii/S2590197426000133
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