Classification of Petrographic Thin Section Images With Depthwise Separable Convolution and Dilated Convolution
To enhance the precision and efficiency of petrographic thin section image classification and reduce the subjectivity resulting from manual classification methods, a new classification model (DC-PC-Dilated-IR-V2) in term of the deep convolutional network is constructed in this study. In the DC-PC-Di...
| الحاوية / القاعدة: | IEEE Access |
|---|---|
| المؤلفون الرئيسيون: | , , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
IEEE
2025-01-01
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ieeexplore.ieee.org/document/10879401/ |
