Deep convolutional neural networks as a geological image classification tool-Reference-Cited by-同舟云学术

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Deep convolutional neural networks as a geological image classification tool

Published:2019-06-30 Issue:2 Volume:17 Page:4-9
ISSN:1543-8740
Container-title:The Sedimentary Record
language:
Short-container-title:Sed Record

Author:

Pires de Lima Rafael,Bonar Alicia,Coronado David Duarte,Marfurt Kurt,Nicholson Charles

Publisher

Society for Sedimentary Geology

Cited by 49 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. RockDNet: Deep Learning Approach for Lithology Classification;Applied Sciences;2024-06-25

2. The exploration of the transfer learning technique for Globotruncanita genus against the limited low-cost light microscope images;Signal, Image and Video Processing;2024-06-12

3. Combining “Deep Learning” and Physically Constrained Neural Networks to Derive Complex Glaciological Change Processes from Modern High-Resolution Satellite Imagery: Application of the GEOCLASS-Image System to Create VarioCNN for Glacier Surges;Remote Sensing;2024-05-23

4. Experiments on image data augmentation techniques for geological rock type classification with convolutional neural networks;Journal of Rock Mechanics and Geotechnical Engineering;2024-05

5. Optimizing Underbalanced Coiled Tubing Drilling Monitoring Via Advanced In-Line Sensing AI Framework;Day 1 Mon, April 22, 2024;2024-04-22

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