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Classification of plutonic rock types using thin section images with deep transfer learning
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Thông tin tài liệu:
Classification of rocks is one of the basic parts of geological research and is a difficult task due to the heterogeneous properties of rocks. This process is time consuming and requires sufficiently knowledgeable and experienced specialists in the field of petrography. This paper has a novelty in classifying plutonic rock types for the first time using thin section images; and proposes an approach that uses the deep learning method for automatic classification of 12 types of plutonic rocks. Convolutional neural network based DenseNet121, which is one of the deep learning architectures, is used to extract the features from thin section images of rocks; and the classification process is carried out with a single layer fully connected neural network.
Tìm kiếm theo từ khóa liên quan:
Journal of Earth Sciences Rock classification Plutonic rocks Deep transfer learning Convolutional neural networksTài liệu liên quan:
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