Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys
Zeyu Xia, Kan Ma, Sibo Cheng, Thomas Blackburn, Ziling Peng, Ke‐Wei Zhu, Weihang Zhang, Dunhui Xiao, Alexander J. Knowles, Rossella Arcucci
Abstract
1-score. This model forms a useful tool to aid alloy development microstructure examinations, and offers significant advantages to address the large datasets associated with high-throughput alloy development approaches.
Topics & Concepts
ChromiumArtificial neural networkIdentification (biology)Stage (stratigraphy)Materials scienceMetallurgyArtificial intelligenceComputer scienceGeologyBiologyBotanyPaleontologyIndustrial Vision Systems and Defect DetectionNuclear Physics and ApplicationsNon-Destructive Testing Techniques