Bridging the physical-digital divide: a deep learning paradigm shift in surface reconstruction for intelligent reverse engineering

Key Points

• Surface reconstruction accuracy improves significantly with deep learning methods, enhancing digital model creation.
• Incorporating data augmentation improved performance metrics by 30%, showcasing deep learning's potential.
• Observational analysis of various neural network architectures revealed their effectiveness in reverse engineering tasks.
• This work supports the integration of intelligent systems, paving the way for advanced applications in engineering.