UNIST professor enables AI to study summarized 3D data

A professor at the Ulsan National Institute of Science and Technology (UNIST) has developed a new technology that allows artificial intelligence (AI) models to study 3D data in a “summarized” form while still achieving a high level of accuracy, reducing both time and cost in 3D data analysis. Shim Jae-young and his team at the UNIST AI Graduate School in Ulsan said Monday that they have developed a “dataset distillation” technology for large-scale 3D data. The technology extracts the core of a given dataset and compares it with the original to retain completeness, enabling effective compression of a 3D point cloud — data composed of randomly distributed dots representing an object — without sacrificing accuracy during analysis. Shim developed the technology after finding that summarizing a 3D point cloud for AI training is particularly difficult. Because the dots in a point cloud are arranged in a random, orderless manner and often represent objects rotated at various angles, AI systems struggle to extract a reliable 3D summary and frequently mismatch it with the original dWeiter zum vollständigen Artikel bei Korea Times Weiter zum vollständigen Artikel bei Korea Times