5 papers
A Synthetic 3D Gear Dataset for Manufacturing Quality Inspection (MFGNet-Gear)
Ruo-Syuan Mei, Chenhui Shao
Quality control in smart manufacturing increasingly relies on data-driven methods, particularly deep learning, to automate the inspection of manufactured parts. Recent advances in…
Adaptive few-shot learning for robust part quality classification in two-photon lithography
Sixian Jia, Ruo-Syuan Mei, Chenhui Shao
Two-photon lithography (TPL) is an advanced additive manufacturing (AM) technique for fabricating high-precision micro-structures. While computer vision (CV) is proofed for automat…
Near-Field Perception for Safety Enhancement of Autonomous Mobile Robots in Manufacturing Environments
Li-Wei Shih, Ruo-Syuan Mei, Jesse Heidrich +6
Near-field perception is essential for the safe operation of autonomous mobile robots (AMRs) in manufacturing environments. Conventional ranging sensors such as light detection and…
EfficientFlow: Efficient Equivariant Flow Policy Learning for Embodied AI
Jianlei Chang, Ruofeng Mei, Wei Ke +1
Generative modeling has recently shown remarkable promise for visuomotor policy learning, enabling flexible and expressive control across diverse embodied AI tasks. However, existi…
Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance
Ruo-Syuan Mei, Sixian Jia, Guangze Li +6
Machine learning, particularly deep learning, is transforming industrial quality inspection. Yet, training robust machine learning models typically requires large volumes of high-q…