U-Net

Yufeng Bian1, Jiangtao Zheng1, Tian Tian1

  • 1State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources, China University of Mining and Technology at Beijing, Beijing 100083, China; School of Mechanics and Civil Engineering, China University of Mining and Technology at Beijing, Beijing 100083, China.

PubMed
概括

精确地从煤炭CT图像中提取断裂对于了解流体运输至关重要. 这项研究使用超分辨率和U-Net细分增强了微碎裂识别,改善了透性预测.