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20212026
most citedPaveSAM Segment Anything for Pavement Distress

20 citations · 102 across the 42 of their papers we have counts for

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10 papers · 1 filter

cs.CV2023★ 4 cited

Image2PCI -- A Multitask Learning Framework for Estimating Pavement Condition Indices Directly from Images

Neema Jakisa Owor, Hang Du, Abdulateef Daud +2

The Pavement Condition Index (PCI) is a widely used metric for evaluating pavement performance based on the type, extent and severity of distresses detected on a pavement surface.…

cs.CV2023

Edge Computing-Enabled Road Condition Monitoring: System Development and Evaluation

Abdulateef Daud, Mark Amo-Boateng, Neema Jakisa Owor +2

Real-time pavement condition monitoring provides highway agencies with timely and accurate information that could form the basis of pavement maintenance and rehabilitation policies…

cs.CV2023★ 2 cited

GazeGNN: A Gaze-Guided Graph Neural Network for Chest X-ray Classification

Bin Wang, Hongyi Pan, Armstrong Aboah +7

Eye tracking research is important in computer vision because it can help us understand how humans interact with the visual world. Specifically for high-risk applications, such as…

cs.CV2023★ 8 cited

GazeSAM: What You See is What You Segment

Bin Wang, Armstrong Aboah, Zheyuan Zhang +1

This study investigates the potential of eye-tracking technology and the Segment Anything Model (SAM) to design a collaborative human-computer interaction system that automates med…

cs.CV2023★ 5 cited

Real-Time Helmet Violation Detection Using YOLOv5 and Ensemble Learning

Geoffery Agorku, Divine Agbobli, Vuban Chowdhury +4

The proper enforcement of motorcycle helmet regulations is crucial for ensuring the safety of motorbike passengers and riders, as roadway cyclists and passengers are not likely to…

cs.CV2023

SigSegment: A Signal-Based Segmentation Algorithm for Identifying Anomalous Driving Behaviours in Naturalistic Driving Videos

Kelvin Kwakye, Younho Seong, Armstrong Aboah +1

In recent years, distracted driving has garnered considerable attention as it continues to pose a significant threat to public safety on the roads. This has increased the need for…

cs.CV2023★ 1 cited

DeepSegmenter: Temporal Action Localization for Detecting Anomalies in Untrimmed Naturalistic Driving Videos

Armstrong Aboah, Ulas Bagci, Abdul Rashid Mussah +2

Identifying unusual driving behaviors exhibited by drivers during driving is essential for understanding driver behavior and the underlying causes of crashes. Previous studies have…

cs.CV2023★ 15 cited

Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8

Armstrong Aboah, Bin Wang, Ulas Bagci +1

Traffic safety is a major global concern. Helmet usage is a key factor in preventing head injuries and fatalities caused by motorcycle accidents. However, helmet usage violations c…

cs.CV2023★ 12 cited

Real-Time Helmet Violation Detection in AI City Challenge 2023 with Genetic Algorithm-Enhanced YOLOv5

Elham Soltanikazemi, Ashwin Dhakal, Bijaya Kumar Hatuwal +3

This research focuses on real-time surveillance systems as a means for tackling the issue of non-compliance with helmet regulations, a practice that considerably amplifies the risk…

cs.CV2023★ 3 cited

AI-Based Framework for Understanding Car Following Behaviors of Drivers in A Naturalistic Driving Environment

Armstrong Aboah, Abdul Rashid Mussah, Yaw Adu-Gyamfi

The most common type of accident on the road is a rear-end crash. These crashes have a significant negative impact on traffic flow and are frequently fatal. To gain a more practica…