25 citations · 41 across the 10 of their papers we have counts for
10 papers
A Multitask Deep Learning Model for Parsing Bridge Elements and Segmenting Defect in Bridge Inspection Images
Chenyu Zhang, Muhammad Monjurul Karim, Ruwen Qin
The vast network of bridges in the United States raises a high requirement for maintenance and rehabilitation. The massive cost of manual visual inspection to assess bridge conditi…
An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving Videos
Muhammad Monjurul Karim, Ruwen Qin, Zhaozheng Yin
Detecting dangerous traffic agents in videos captured by vehicle-mounted dashboard cameras (dashcams) is essential to facilitate safe navigation in a complex environment. Accident-…
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 semi-supervised self-training method to develop assistive intelligence for segmenting multiclass bridge elements from inspection videos
Muhammad Monjurul Karim, Ruwen Qin, Zhaozheng Yin +1
Bridge inspection is an important step in preserving and rehabilitating transportation infrastructure for extending their service lives. The advancement of mobile robotic technolog…
Crash Report Data Analysis for Creating Scenario-Wise, Spatio-Temporal Attention Guidance to Support Computer Vision-based Perception of Fatal Crash Risks
Yu Li, Muhammad Monjurul Karim, Ruwen Qin
Reducing traffic fatalities and serious injuries is a top priority of the US Department of Transportation. The computer vision (CV)-based crash anticipation in the near-crash phase…
A Virtual Reality-based Training and Assessment System for Bridge Inspectors with an Assistant Drone
Yu Li, Muhammad Monjurul Karim, Ruwen Qin
Over 600,000 bridges in the U.S. must be inspected every two years to identify flaws, defects, or potential problems that may need follow-up maintenance. Bridge inspection has adop…
A Gaze Data-based Comparative Study to Build a Trustworthy Human-AI Collaboration in Crash Anticipation
Yu Li, Muhammad Monjurul Karim, Ruwen Qin
Vehicles with a safety function for anticipating crashes in advance can enhance drivers' ability to avoid crashes. As dashboard cameras have become a low-cost sensor device accessi…
Towards explainable artificial intelligence (XAI) for early anticipation of traffic accidents
Muhammad Monjurul Karim, Yu Li, Ruwen Qin
Traffic accident anticipation is a vital function of Automated Driving Systems (ADSs) for providing a safety-guaranteed driving experience. An accident anticipation model aims to p…
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…