A deep learning-based method for segmentation and quantitative characterization of microstructures in weathering steel from sequential scanning electron microscope images

• Published in: Journal of iron and steel research, international Vol. 29; no. 5; pp. 836 - 845
• Main Authors: Han, Bing, Wan, Wei-hao, Sun, Dan-dan, Dong, Cai-chang, Zhao, Lei, Wang, Hai-zhou
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 01.05.2022
• Subjects: Applied and Technical Physics; Engineering; Machines; Manufacturing; Materials Engineering; Materials Science; Metallic Materials; Original Paper; Physical Chemistry; Processes; Deep learning; High-throughput; Segmentation; Rapid acquisition; Sequential image; Quantitative characterization; Microstructure

Microstructural classification is typically done manually by human experts, which gives rise to uncertainties due to subjectivity and reduces the overall efficiency. A high-throughput characterization is proposed based on deep learning, rapid acquisition technology, and mathematical statistics for t...