| 基于岩石图像深度学习的多尺度岩性识别 |
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| 引用本文： | 马泽栋,马雷,李科,姚伟,王培丁,王鑫宇.基于岩石图像深度学习的多尺度岩性识别[J].地质科技通报,2022,41(6):316-322. |
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| 作者姓名： | 马泽栋 马雷 李科 姚伟 王培丁 王鑫宇 |
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| 作者单位： | 合肥工业大学资源与环境工程学院, 合肥 230009 |
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| 基金项目： | 国家自然科学基金项目41831289国家自然科学基金项目42072276大学生创新创业训练计划项目202010359061 |
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| 摘 要： | 岩性识别作为人工智能和大数据在地质工程细分领域的实践应用方向, 可以为相关人员野外地质工作提供有效助力。为了更好地促进岩性识别在专业领域的应用, 通过对巢湖北部山区的岩石图像采集、数据预处理、迁移学习、网络搭建、网络训练及模型测试等步骤, 实现了基于岩石图像的大数据深度学习识别; 并在归纳总结前人工作的基础上, 提出了多尺度岩性识别方法。根据岩石细观图像建立多尺度模型并赋予一定权重, 与岩石识别模型共同识别得到综合结果, 对岩石岩性整体识别的同时兼顾局部纹理、粒径等细观信息。研究结果表明, 本模型对岩石识别的适用性强, 多尺度方法对于提高识别结果的正确率具有一定的帮助, 模型的测试正确率达到95%以上, 能很好地识别岩石岩性。
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| 关 键 词： | 深度学习 岩性识别 多尺度 权重 图像 |
| 收稿时间： | 2021-06-28 |
Multi-scale lithology recognition based on deep learning of rock images |
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| Affiliation: | School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230009, China |
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| Abstract: | Lithology recognition through artificial intelligence and big data can provide effective assistance to relevant personnel in field investigations.To better promote the application of lithology recognition in professional fields, the deep learning recognition of big data based on rock images were performed through the steps of rock image acquisition, data preprocessing, migration learning, network building, network training and model testing in the northern mountain area of Chaohu.Based on previous work, a multi-scale lithologic identification method is proposed. A multi-scale model is established and given a certain weight according to the rock meso image.The comprehensive results are obtained by identification with the rock identification model. The local texture, particle size and other mesoscale information were used in the overall identification of rock lithology.The results show that the multi-scale method is helpful to improve the identification results. The accuracy of the model is above 95%, which can well identify the rock lithology. |
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