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

5 citations · 13 across the 16 of their papers we have counts for

collaborators

16 papers

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

A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning

Joshua Kofi Asamoah, Blessing Agyei Kyem, Armstrong Aboah

City-wide traffic forecasting is important for congestion management, route guidance, and intelligent transportation systems, but accurate prediction remains challenging when futur…

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…

cs.CV2026

Class-Adaptive Cooperative Perception for Multi-Class LiDAR-based 3D Object Detection in V2X Systems

Blessing Agyei Kyem, Joshua Kofi Asamoah, Armstrong Aboah

Cooperative perception allows connected vehicles and roadside infrastructure to share sensor observations, creating a fused scene representation beyond the capability of any single…

cs.CV2026

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…

cs.CV2025★ 2 cited

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…

cs.CV2025

A Unified Detection Pipeline for Robust Object Detection in Fisheye-Based Traffic Surveillance

Neema Jakisa Owor, Joshua Kofi Asamoah, Tanner Wambui Muturi +5

Fisheye cameras offer an efficient solution for wide-area traffic surveillance by capturing large fields of view from a single vantage point. However, the strong radial distortion…

cs.CV2025

Prompt-Guided Spatial Understanding with RGB-D Transformers for Fine-Grained Object Relation Reasoning

Tanner Muturi, Blessing Agyei Kyem, Joshua Kofi Asamoah +5

Spatial reasoning in large-scale 3D environments such as warehouses remains a significant challenge for vision-language systems due to scene clutter, occlusions, and the need for p…

cs.CV2025

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…

cs.CV2025★ 4 cited

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…

cs.CV2025

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…

cs.CV2025

Integrating Travel Behavior Forecasting and Generative Modeling for Predicting Future Urban Mobility and Spatial Transformations

Eugene Denteh, Andrews Danyo, Joshua Kofi Asamoah +3

Transportation planning plays a critical role in shaping urban development, economic mobility, and infrastructure sustainability. However, traditional planning methods often strugg…

cs.CV2025

Context-CrackNet: A Context-Aware Framework for Precise Segmentation of Tiny Cracks in Pavement images

Blessing Agyei Kyem, Joshua Kofi Asamoah, Armstrong Aboah

The accurate detection and segmentation of pavement distresses, particularly tiny and small cracks, are critical for early intervention and preventive maintenance in transportation…

cs.CV2024★ 5 cited

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

Blessing Agyei Kyem, Eugene Kofi Okrah Denteh, Joshua Kofi Asamoah +2

Road infrastructure maintenance in developing countries faces unique challenges due to resource constraints and diverse environmental factors. This study addresses the critical nee…

cs.CV2024★ 2 cited

PaveCap: The First Multimodal Framework for Comprehensive Pavement Condition Assessment with Dense Captioning and PCI Estimation

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

This research introduces the first multimodal approach for pavement condition assessment, providing both quantitative Pavement Condition Index (PCI) predictions and qualitative des…