Abstract:
Large aircraft, as one of the most complex high-end equipment in modern society, is the culmination of interdisciplinary and cross-domain advanced technologies, occupying the top of the manufacturing industry's technology and value chains. With the emergence of a batch of national key equipment such as the Y-20, C919, and Jiaolong-600, China has made breakthrough progress in large aircraft manufacturing and gradually established a relatively complete production and development system. However, due to insufficient technological foundation and compared with international aerospace manufacturing giants, Chinese aviation enterprises have not yet achieved integrated manufacturing and measurement capabilities or effective precision control capabilities. The "high-precision rapid 3D scanning analysis and quality control technology" has become an important factor affecting the development process of large aircraft in China. Geometric deep learning, with its powerful ability to learn geometric features, has shown great potential in the analysis of large aircraft shapes. However, existing network structures lack domain-specific expertise in aviation, there is no publicly available large-scale aircraft 3D dataset, and the latest machine learning technologies have not been deeply integrated into the field of geometric deep learning, making it difficult to comprehensively and efficiently analyze the complex features and stringent accuracy requirements of large aircraft shapes. This report will introduce the interdisciplinary technical issues involved in the analysis of large aircraft shapes.

Biography:
Prof. Mingqiang Wei received his Ph.D. degree (2014) in Computer Science and Engineering from the Chinese University of Hong Kong (CUHK). He is a professor at the School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics (NUAA). He was the recipient of Excellent Youth Fund Project of the National Natural Science Foundation of China in 2023. Before joining NUAA, he served as an assistant professor at Hefei University of Technology, and a postdoctoral fellow at CUHK. He was a recipient of the CUHK Young Scholar Thesis Awards in 2014. He is now an Associate Editor for ACM TOMM, The Visual Computer Journal, Journal of Electronic Imaging, and a Guest Editor for IEEE Transactions on Multimedia. His research interests focus on 3D vision, computer graphics, and deep learning.