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

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