3 citations · 5 across the 4 of their papers we have counts for
6 papers
Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning
Hritam Basak, Zhaozheng Yin
Although unsupervised domain adaptation (UDA) is a promising direction to alleviate domain shift, they fall short of their supervised counterparts. In this work, we investigate rel…
A Deep Neural Network for Multiclass Bridge Element Parsing in Inspection Image Analysis
Chenyu Zhang, Muhammad Monjurul Karim, Zhaozheng Yin +1
Aerial robots such as drones have been leveraged to perform bridge inspections. Inspection images with both recognizable structural elements and apparent surface defects can be col…
A system of vision sensor based deep neural networks for complex driving scene analysis in support of crash risk assessment and prevention
Muhammad Monjurul Karim, Yu Li, Ruwen Qin +1
To assist human drivers and autonomous vehicles in assessing crash risks, driving scene analysis using dash cameras on vehicles and deep learning algorithms is of paramount importa…
A Dynamic Spatial-temporal Attention Network for Early Anticipation of Traffic Accidents
Muhammad Monjurul Karim, Yu Li, Ruwen Qin +1
The rapid advancement of sensor technologies and artificial intelligence are creating new opportunities for traffic safety enhancement. Dashboard cameras (dashcams) have been widel…
3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management
Tianyi Zhao, Kai Cao, Jiawen Yao +6
The pancreatic disease taxonomy includes ten types of masses (tumors or cysts)[20,8]. Previous work focuses on developing segmentation or classification methods only for certain ma…
Multi-Modal Recognition of Worker Activity for Human-Centered Intelligent Manufacturing
Wenjin Tao, Ming C. Leu, Zhaozheng Yin
In a human-centered intelligent manufacturing system, sensing and understanding of the worker's activity are the primary tasks. In this paper, we propose a novel multi-modal approa…