20 citations · 102 across the 42 of their papers we have counts for
6 papers · 1 filter
PaveSAM Segment Anything for Pavement Distress
Neema Jakisa Owor, Yaw Adu-Gyamfi, Armstrong Aboah +1
Automated pavement monitoring using computer vision can analyze pavement conditions more efficiently and accurately than manual methods. Accurate segmentation is essential for quan…
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…
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…
Low-Light Image Enhancement Framework for Improved Object Detection in Fisheye Lens Datasets
Dai Quoc Tran, Armstrong Aboah, Yuntae Jeon +3
This study addresses the evolving challenges in urban traffic monitoring detection systems based on fisheye lens cameras by proposing a framework that improves the efficacy and acc…
Enhancing Traffic Safety with Parallel Dense Video Captioning for End-to-End Event Analysis
Maged Shoman, Dongdong Wang, Armstrong Aboah +1
This paper introduces our solution for Track 2 in AI City Challenge 2024. The task aims to solve traffic safety description and analysis with the dataset of Woven Traffic Safety (W…
3D Object Detection and High-Resolution Traffic Parameters Extraction Using Low-Resolution LiDAR Data
Linlin Zhang, Xiang Yu, Armstrong Aboah +1
Traffic volume data collection is a crucial aspect of transportation engineering and urban planning, as it provides vital insights into traffic patterns, congestion, and infrastruc…