3 citations · 4 across the 5 of their papers we have counts for
5 papers
Automating construction safety inspections using a multi-modal vision-language RAG framework
Chenxin Wang, Elyas Asadi Shamsabadi, Zhaohui Chen +3
Conventional construction safety inspection methods are often inefficient as they require navigating through large volume of information. Recent advances in large vision-language m…
LVLMs as inspectors: an agentic framework for category-level structural defect annotation
Sheng Jiang, Yuanmin Ning, Bingxi Huang +2
Automated structural defect annotation is essential for ensuring infrastructure safety while minimizing the high costs and inefficiencies of manual labeling. A novel agentic annota…
Integration of Large Vision Language Models for Efficient Post-disaster Damage Assessment and Reporting
Zhaohui Chen, Elyas Asadi Shamsabadi, Sheng Jiang +2
Traditional natural disaster response involves significant coordinated teamwork where speed and efficiency are key. Nonetheless, human limitations can delay critical actions and in…
Vision Mamba-based autonomous crack segmentation on concrete, asphalt, and masonry surfaces
Zhaohui Chen, Elyas Asadi Shamsabadi, Sheng Jiang +2
Convolutional neural networks (CNNs) and Transformers have shown advanced accuracy in crack detection under certain conditions. Yet, the fixed local attention can compromise the ge…
Robust feature knowledge distillation for enhanced performance of lightweight crack segmentation models
Zhaohui Chen, Elyas Asadi Shamsabadi, Sheng Jiang +2
Vision-based crack detection faces deployment challenges due to the size of robust models and edge device limitations. These can be addressed with lightweight models trained with k…