7 papers · 1 filter
Multi-Task Crack Foundation Model for Engineering-Reliable Crack Representation and Topology Preservation in Civil Infrastructure
Blessing Agyei Kyem, Joshua Kofi Asamoah, Eugene Denteh +1
Reliable crack assessment requires not only accurate pixel-level masks but also connected crack geometry and confidence estimates that remain stable under domain shift. However, ex…
Hybrid Congestion Classification Framework Using Flow-Guided Attention and Empirical Mode Decomposition
Eugene Kofi Okrah Denteh, Blessing Agyei Kyem, Joshua Kofi Asamoah +1
Accurate traffic congestion classification requires models that jointly capture roadway scene context and non-stationary traffic motion, yet most prior work treats these requiremen…
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…
Self-Supervised Multi-Scale Transformer with Attention-Guided Fusion for Efficient Crack Detection
Blessing Agyei Kyem, Joshua Kofi Asamoah, Eugene Denteh +2
Pavement crack detection has long depended on costly and time-intensive pixel-level annotations, which limit its scalability for large-scale infrastructure monitoring. To overcome…
Demographics-Informed Neural Network for Multi-Modal Spatiotemporal forecasting of Urban Growth and Travel Patterns Using Satellite Imagery
Eugene Kofi Okrah Denteh, Andrews Danyo, Joshua Kofi Asamoah +2
This study presents a novel demographics informed deep learning framework designed to forecast urban spatial transformations by jointly modeling geographic satellite imagery, socio…