MicroCrystalNet: An Efficient and Explainable Convolutional Neural Network for Microcrystal Classification Using Scanning Electron Microscope Petrography

MicroCrystalNet: An Efficient and Explainable Convolutional Neural Network for Microcrystal Classification Using Scanning Electron Microscope Petrography

<p dir="ltr">Morphological characterization of microcrystalline rock textures typically relies upon the visual interpretation and manual measurement of scanning electron microscopy (SEM) imagery: a practice fraught with subjectivity, inefficiency, sampling bias, and data loss. We int...

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Bibliographic Details
Main Author: Mohammed Yaqoob (344668) (author)
Other Authors: Mohammed Yusuf Ansari (22047911) (author), Mohammed Ishaq (22302736) (author), Issac Sujay Anand John Jayachandran (22457725) (author), Mohammed S. Hashim (21586770) (author), Thomas Daniel Seers (21797324) (author)
Published: 2025
Subjects:
Engineering
Resources engineering and extractive metallurgy
Information and computing sciences
Artificial intelligence
Machine learning
Carbonate characterization
classification
deep learning
petrography
segmentation
SEM imaging
materials science
Rocks
Scanning electron microscopy
Crystals
Pipelines
Feature extraction
Photomicrography
Visualization
Media
Surface topography
Surface morphology
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