7 papers
Vision-Language Foundation Models for Comprehensive Automated Pavement Condition Assessment
Blessing Agyei Kyem, Joshua Kofi Asamoah, Anthony Dontoh +1
General-purpose vision-language models demonstrate strong performance in everyday domains but struggle with specialized technical fields requiring precise terminology, structured r…
A Contextual Analysis of Driver-Facing and Dual-View Video Inputs for Distraction Detection in Naturalistic Driving Environments
Anthony Dontoh, Stephanie Ivey, Armstrong Aboah
Despite increasing interest in computer vision-based distracted driving detection, most existing models rely exclusively on driver-facing views and overlook crucial environmental c…
PaveSync: A Unified and Comprehensive Dataset for Pavement Distress Analysis and Classification
Blessing Agyei Kyem, Joshua Kofi Asamoah, Anthony Dontoh +3
Automated pavement defect detection often struggles to generalize across diverse real-world conditions due to the lack of standardized datasets. Existing datasets differ in annotat…
Task-Specific Dual-Model Framework for Comprehensive Traffic Safety Video Description and Analysis
Blessing Agyei Kyem, Neema Jakisa Owor, Andrews Danyo +6
Traffic safety analysis requires complex video understanding to capture fine-grained behavioral patterns and generate comprehensive descriptions for accident prevention. In this wo…
Visual Dominance and Emerging Multimodal Approaches in Distracted Driving Detection: A Review of Machine Learning Techniques
Anthony Dontoh, Stephanie Ivey, Logan Sirbaugh +2
Distracted driving continues to be a significant cause of road traffic injuries and fatalities worldwide, even with advancements in driver monitoring technologies. Recent developme…
An Improved ResNet50 Model for Predicting Pavement Condition Index (PCI) Directly from Pavement Images
Andrews Danyo, Anthony Dontoh, Armstrong Aboah
Accurately predicting the Pavement Condition Index (PCI), a measure of roadway conditions, from pavement images is crucial for infrastructure maintenance. This study proposes an en…