no code implementations • 12 Aug 2023 • Muhammad Monjurul Karim, Ruwen Qin, Yinhai Wang
To ensure the safe and efficient navigation of autonomous vehicles and advanced driving assistance systems in complex traffic scenarios, predicting the future bounding boxes of surrounding traffic agents is crucial.
1 code implementation • 14 Jul 2023 • Chenyu Zhang, Zhaozheng Yin, Ruwen Qin
Efficiently monitoring the condition of civil infrastructure requires automating the structural condition assessment in visual inspection.
1 code implementation • 16 Sep 2022 • Muhammad Monjurul Karim, Ruwen Qin, Zhaozheng Yin
To this end, this paper proposes an attention-guided multistream feature fusion network (AM-Net) to localize dangerous traffic agents from dashcam videos.
1 code implementation • 6 Sep 2022 • Chenyu Zhang, Muhammad Monjurul Karim, Ruwen Qin
Quantitative and qualitative results from evaluating the developed multitask deep model demonstrate its advantages over the single-task-based model not only in performance (2. 59% higher mIoU on bridge parsing and 1. 65% on corrosion segmentation) but also in computational time and implementation capability.
no code implementations • 5 Sep 2022 • Chenyu Zhang, Muhammad Monjurul Karim, Zhaozheng Yin, Ruwen Qin
Aerial robots such as drones have been leveraged to perform bridge inspections.
1 code implementation • 8 Jul 2022 • Yu Li, Anisha Parsan, Bill Wang, Penghao Dong, Shanshan Yao, Ruwen Qin
A base model for a group of five authorized subjects is trained and tested on the inspection keyword dataset collected by this study.
no code implementations • 20 Dec 2021 • Wenjin Tao, Haodong Chen, Md Moniruzzaman, Ming C. Leu, Zhaozheng Yi, Ruwen Qin
Secondly, an attention-based fusion mechanism is developed to learn the importance of sensors at different body locations and to generate an attentive feature representation.
no code implementations • 10 Sep 2021 • Muhammad Monjurul Karim, Ruwen Qin, Zhaozheng Yin, Genda Chen
This paper is motivated to develop an assistive intelligence model for segmenting multiclass bridge elements from inspection videos captured by an aerial inspection platform.
no code implementations • 6 Sep 2021 • Yu Li, Muhammad Monjurul Karim, Ruwen Qin
Then, exploratory analysis of location- and time-related variables of the crash report data suggests reducing fatal crashes to spatially defined groups.
1 code implementation • 31 Jul 2021 • Muhammad Monjurul Karim, Yu Li, Ruwen Qin
It confirms that the Grad-CAM chosen by this study can generate high-quality, human-interpretable saliency maps (with 1. 23 Normalized Scanpath Saliency) for explaining the crash anticipation decision.
1 code implementation • 18 Jun 2021 • Muhammad Monjurul Karim, Yu Li, Ruwen Qin, Zhaozheng Yin
Visual cues for predicting a future accident are embedded deeply in dashcam video data.
Ranked #1 on Accident Anticipation on CCD
2 code implementations • 18 Jun 2021 • Muhammad Monjurul Karim, Yu Li, Ruwen Qin, Zhaozheng Yin
The paper further evaluates the performance of the Multi-Net and the efficiency of the developed system.