Synthetic material for AI training Using a game engine to generate synthetic training data offers significant advantages for AI training in image classification, object detection, and animation classification. Synthetic data, created in controlled virtual environments, allows for the generation of large, diverse, and perfectly labeled datasets. This contrasts with human-labeled material, which is often expensive, […]
Two papers were accepted in the 2024 International Conference on eXtended Reality. XR Salento 2024. Tang, Ming, Mikhail Nikolaenko, Evv Boerwinkle, Samuel Obafisoye, Aayush Kumar, Mohsen Rezayat, Sven Lehmann, and Tamara Lorenz. “Evaluation of the Effectiveness of Traditional Training vs. Immersive Training: A Case Study of Building Safety & Emergency Training.” Paper accepted at the International Conference […]
Automatic Scene Creation for Augmented Reality Work Instructions Using Generative AI. Siemens. PI. Ming Tang. co-PI: Tianyu Jiang. $25,000. UC. 4/1/2024-12/31/2024 Sponsor: Siemens through UC MME Industry 4.0/5.0 Institute
Nancy Daraiseh, Ming Tang, Mikhail Nikolaenko . Using Virtual Reality to Enhance Behavioral Staff Training for Interacting with Aggressive Psychiatric Patients. The 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024). Nice, France, July 24-27, 2024. Objective: To conduct a pilot study to enhance staff training and confidence when interacting with aggressive psychiatric […]
XR-Lab’s project was selected to join the Undergraduates Pursuing Research in Science and Engineering (UPRISE) Program UNDERGRADUATE SUMMER RESEARCH PROGRAM IN SCIENCE AND ENGINEERING May 6 – July 26, 2024 Project title: Reinforcement Learning (RL) system in Game Engine This project proposes the development of a sophisticated reinforcement learning (RL) system utilizing the robust […]
