activity
20202023
most citedA semi-supervised self-training method to develop assistive intelligence for segmenting multiclass bridge elements from inspection videos

25 citations · 28 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2023★ 2 cited

Advancements in Repetitive Action Counting: Joint-Based PoseRAC Model With Improved Performance

Haodong Chen, Ming C. Leu, Md Moniruzzaman +2

Repetitive counting (RepCount) is critical in various applications, such as fitness tracking and rehabilitation. Previous methods have relied on the estimation of red-green-and-blu…

cs.CV2022

Cross-domain Microscopy Cell Counting by Disentangled Transfer Learning

Zuhui Wang

Microscopy images from different imaging conditions, organs, and tissues often have numerous cells with various shapes on a range of backgrounds. As a result, designing a deep lear…

cs.CV2022★ 1 cited

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-…

cs.CV2021★ 25 cited

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…

stat.AP2021

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…

cs.MM2020

Detecting Medical Misinformation on Social Media Using Multimodal Deep Learning

Zuhui Wang, Zhaozheng Yin, Young Anna Argyris

In 2019, outbreaks of vaccine-preventable diseases reached the highest number in the US since 1992. Medical misinformation, such as antivaccine content propagating through social m…