Investigation into the feature extraction module and lightweight network for rock image analysis
Authors:
- 30 January 2026
- journal article
- research article
- Published by Springer Nature in Earth Science Informatics
- Vol. 19 (2) , 18
Abstract
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Funding Information
- Top-notch Young Teachers' Innovation Ability Cultivation Project (2652023004)
- China Coal Geology Administration (No. ZMKJ-2023-JBGS08)
This publication has 28 references indexed in Scilit:
- A multi-module fusion network for coal-rock interface recognitionMeasurement, 2025
- Hierarchical intelligent lithology recognition for thin section images using enhanced DenseNetEarth Science Informatics, 2024
- Applied machine learning-based models for determining the magnitude of pore pressure and minimum horizontal stressArabian Journal of Geosciences, 2024
- Applied machine learning-based models for predicting the geomechanical parameters using logging dataJournal of Petroleum Exploration and Production Technology, 2023
- A real-time and efficient surface defect detection method based on YOLOv4Journal of Real-Time Image Processing, 2023
- Multi-input Vision Transformer with Similarity Matching2023
- Deep learning of rock microscopic images for intelligent lithology identification: Neural network comparison and selectionJournal of Rock Mechanics and Geotechnical Engineering, 2022
- Deep learning based classification of rock structure of tunnel faceGeoscience Frontiers, 2021
- Deep network in networkNeural Computing and Applications, 2020
- Development and Application of Artificial Neural NetworkWireless Personal Communications, 2017