Implementation of deep learning-based segmentation for quantitative microstructure analysis and 3D reconstruction in aluminum alloys

Key Points

• The aim is to explore deep learning techniques for analyzing the microstructure of aluminum alloys through segmentation and 3D reconstruction.
• Applied deep learning algorithms for image segmentation.
• Conducted quantitative microstructure analysis on aluminum alloys.
• Performed 3D reconstruction based on segmented data.
• Achieved improved accuracy in microstructure segmentation.
• Facilitated detailed 3D reconstructions of aluminum alloys.
• Enabled enhanced quantitative analysis compared to traditional methods.