Author-submitted data information
| ID | 707 |
| Title | Algorithm and results for classification of rock thin section images |
| Creator | Pengfei Lv |
| Subject | Machine learning, Rock thin section images, Solid Earth |
| Publisher | Xiukuan Zhao |
| Description | This algorithm is implemented in MATLAB and leverages transfer learning with convolutional neural networks (CNNs). It incorporates a self-attention layer to boost the feature extraction capabilities specifically for rock thin image classification. This approach is particularly well-suited for classification tasks on small-scale datasets. AlexNet: Transfer learning using the AlexNet pretrained model. MSA_AlexNet: Transfer learning using the MSA-AlexNet pretrained model. VGG16: Transfer learning using the VGG16 pretrained model. MSA_VGG16: Transfer learning using the MSA-VGG16 pretrained model. More details please see README.md |
| Contributor | |
| Date | March 19, 2025 |
| Type | |
| Format | *.m available in MATLAB |
| URL | http://www.geophys.ac.cn/ArticleData/20250414ClassificationAlgorithm.zip |
| DOI | 10.12197/2025GA008 |
| Source | |
| Language | eng |
| Relation | |
| Coverage | |
| Rights | Institute of Geology and Geophysics, Chinese Academy of Sciences |