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20242026
most citedAdvancing Pavement Distress Detection in Developing Countries: A Novel Deep Learning Approach with Locally-Collected Datasets

5 citations · 13 across the 10 of their papers we have counts for

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cs.CV2026

Synthetic-to-Real Text-Based Person Anomaly Search via Multi-Model Retrieval Fusion and Cross-Encoder Reranking

Eugene Denteh, Blessing Agyei Kyem, Andrews Danyo +5

Text-based person anomaly search requires a model to retrieve individuals from a large image gallery using natural-language descriptions of both appearance and behavior. This task…

cs.CV2026

StateBridge: Phase- and Track-Grounded Reasoning for Synthetic-to-Real Traffic Video Captioning and VQA

Blessing Agyei Kyem, Richard Dzinyela, Joshua Kofi Asamoah +5

Traffic safety videos provide rich evidence for understanding interactions between pedestrians and vehicles, but synthetic-to-real evaluation makes this setting challenging because…

cs.AI2026

A Dynamic Scene Interaction Reasoning Framework for Scene-level Lane-Change Intention and Trajectory Prediction of Multiple Interacting Vehicles

Joshua Kofi Asamoah, Blessing Agyei Kyem, Eugene Denteh +1

Safe motion planning in advanced driver-assistance systems and autonomous vehicles requires an accurate understanding of how the surrounding traffic scene is likely to evolve. Howe…

cs.CV2026

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…

cs.CV2026

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…