rock images for image processing
Reconstructing high fidelity digital rock images using deep
2022.3.11 In this study, we present applications of several convolutional neural networks (CNN) for rapid image denoising, deblurring and super-resolving digital rock
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Deep learning of rock microscopic images for ... - ScienceDirect
2022.8.1 To improve the automation of the whole identification process and reduce the difficulty of image processing, deep learning has been gradually applied to
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A method of blasted rock image segmentation based on improved
2022.5.3 The algorithm first obtains the binary image after image pre-processing and performs distance transformation; then by selecting the appropriate gray threshold,
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Automatic segmentation tool for 3D digital rocks by deep
2021.9.27 For each rock image and each noise type we have generated around 50 synthetic new images with different noise levels. We have then processed all of them
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Frontiers Rock image classification using deep
2023.1.16 Rock image classification is a significant part of geological research. Compared with traditional image classification methods, rock image classification methods based on deep learning models have the
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(PDF) Applications of Physically Accurate Deep Learning for
PDF On Jan 28, 2022, Yufu Niu published Applications of Physically Accurate Deep Learning for Processing Digital Rock Images Find, read and cite all the research you
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Segmentation of digital rock images using texture analysis and
Image segmentation is an important part of the standard digital rock physics (DRP) workows. In this paper, we present ground-truthing of digital rock images using texture
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Flow-Based Characterization of Digital Rock Images Using Deep
2021.3.1 The objective of this paper is to present a comprehensive literature review on petrophysical properties estimation from dry rock images using different ML
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Digital Rock Physics and Machine Learning - Frontiers
Digital rock physics (DRP) is an effective approach to characterize pore microstructures and predict effective physical properties of porous medium using digital image data obtained
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Automated image processing algorithms can improve the quality, efficiency, and consistency of classifying the morphology of heterogeneous carbonate rock and deal
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