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...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IEEE
2025-01-01
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| coleção: | IEEE Access |
| Assuntos: | |
| Acesso em linha: | https://ieeexplore.ieee.org/document/10879401/ |
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