.png){kind=icon}
返回
Generic dual-phase classification models through deep learning semantic segmentation method and image gray-level optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.scriptamat.2023.115948.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Two generic deep learning models for automatic classification of dual-phase microstructures were constructed through the semantic segmentation method of DeepLab v3+, based on a small data including 6 SEM images of the U-2Nb alloys with dual-phase microstructure and the corresponding ground truth. One model is suitable for directly classifying images with different gray-level ranges and has a good average classifying accuracy. Although the other model is only suitable for a specific gray-level range, but it cost less for training and can realize a higher classifying accuracy than the former model combined with optimal gray-level adjustment for images. The two DL models were applied to classify dual-phase microstructures of different morphologies and materials, including the isothermal cooling and continuous cooling microstructures of U-2Nb alloys, and the dual-phase steel microstructure, the results of which manifest that both the two models have high classification accuracy and excellent general applicability.
Keyword:
Dual-phase
Microstructure classification
Semantic segmentation
Deep learning
Gray-level range
期刊
IF:
5.6
论文数:
1.6W
被引数:
5.1W
机构
引用论文
A generic high-throughput microstructure classification and quantification method for regular SEM images of complex steel microstructures combining EBSD labeling and deep learning结合EBSD标记和深度学习的复杂钢组织常规SEM图像的通用高通量组织分类和量化方法
OAAI
OAAI分享收藏Bi-directional prediction of structural characteristics and effective thermal conductivities of composite fuels through learning from finite element simulation results.png)
MATERIALS & DESIGNOAAI
MATERIALS & DESIGNIF7.9
OAAI分享收藏Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels深度学习用于钢材高级STEM图像中缺陷的语义分割SCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏Deep learning-assisted microstructural analysis of Ni/YSZ anode composites for solid oxide fuel cells深度学习辅助的固体氧化物燃料电池Ni/YSZ阳极复合材料微结构分析
PREAI
分享收藏分享收藏Interface structure of (130) twin in the U-14.0 at.% Nb alloy: an experimental and theoretical studySCRIPTA MATERIALIA
SCRIPTA MATERIALIAIF5.6
PREAI
分享收藏
查看更多内容