activity
20192026
most citedDeep Machine Learning Approach to Develop a New Asphalt Pavement Condition Index

292 citations · 527 across the 24 of their papers we have counts for

collaborators

25 papers

cs.CV2026

A VLM-Enhanced Framework for Comprehensive Traffic Sign Condition Assessment Integrating Daytime Visual Performance and Nighttime Retroreflectivity Evaluation

Linlin Zhang, Neema Jakisa Owor, Xiang Yu +2

Traffic signs are crucial components of road safety, serving as visual tools under all lighting conditions. The Manual on Uniform Traffic Control Devices (MUTCD) specifies daytime…

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.CV2024★ 20 cited

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…

cs.CV2024★ 2 cited

Application of 2D Homography for High Resolution Traffic Data Collection using CCTV Cameras

Linlin Zhang, Xiang Yu, Abdulateef Daud +2

Traffic cameras remain the primary source data for surveillance activities such as congestion and incident monitoring. To date, State agencies continue to rely on manual effort to…

cs.CV2024★ 4 cited

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…

cs.CV2023★ 4 cited

Image2PCI -- A Multitask Learning Framework for Estimating Pavement Condition Indices Directly from Images

Neema Jakisa Owor, Hang Du, Abdulateef Daud +2

The Pavement Condition Index (PCI) is a widely used metric for evaluating pavement performance based on the type, extent and severity of distresses detected on a pavement surface.…

cs.CV2023

Edge Computing-Enabled Road Condition Monitoring: System Development and Evaluation

Abdulateef Daud, Mark Amo-Boateng, Neema Jakisa Owor +2

Real-time pavement condition monitoring provides highway agencies with timely and accurate information that could form the basis of pavement maintenance and rehabilitation policies…

cs.SE2023

MobiScout: A Scalable Cloud-Based Driving and Activity Monitoring Platform Featuring an IOS App and a WatchOS Extension

Kojo Konadu Adu-Gyamfi, Karo Ahmadi-Dehrashid, Yaw Okyere Adu-Gyamfi +2

MobiScout is an iOS software that monitors users' driving habits and physiological conditions while on the road. The Mobiscout app was created to provide a low-cost next-generation…

cs.DC2023★ 1 cited

Accelerating Statewide Connected Vehicles Big (Sensor Fusion) Data ETL Pipelines on GPUs

Abdul Rashid Mussah, Maged Shoman, Mark Amo-Boateng +1

Real-time traffic and sensor data from connected vehicles have the potential to provide insights that will lead to the immediate benefit of efficient management of the transportati…

cs.CV2023★ 1 cited

DeepSegmenter: Temporal Action Localization for Detecting Anomalies in Untrimmed Naturalistic Driving Videos

Armstrong Aboah, Ulas Bagci, Abdul Rashid Mussah +2

Identifying unusual driving behaviors exhibited by drivers during driving is essential for understanding driver behavior and the underlying causes of crashes. Previous studies have…

cs.CV2023★ 15 cited

Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8

Armstrong Aboah, Bin Wang, Ulas Bagci +1

Traffic safety is a major global concern. Helmet usage is a key factor in preventing head injuries and fatalities caused by motorcycle accidents. However, helmet usage violations c…

cs.CV2023★ 3 cited

AI-Based Framework for Understanding Car Following Behaviors of Drivers in A Naturalistic Driving Environment

Armstrong Aboah, Abdul Rashid Mussah, Yaw Adu-Gyamfi

The most common type of accident on the road is a rear-end crash. These crashes have a significant negative impact on traffic flow and are frequently fatal. To gain a more practica…

cs.CV2022

GC-GRU-N for Traffic Prediction using Loop Detector Data

Maged Shoman, Armstrong Aboah, Abdulateef Daud +1

Because traffic characteristics display stochastic nonlinear spatiotemporal dependencies, traffic prediction is a challenging task. In this paper develop a graph convolution gated…

cs.CV2022★ 1 cited

Driver Maneuver Detection and Analysis using Time Series Segmentation and Classification

Armstrong Aboah, Yaw Adu-Gyamfi, Senem Velipasalar Gursoy +3

The current paper implements a methodology for automatically detecting vehicle maneuvers from vehicle telemetry data under naturalistic driving settings. Previous approaches have t…

cs.CV2022★ 6 cited

The 1st Data Science for Pavements Challenge

Ashkan Behzadian, Tanner Wambui Muturi, Tianjie Zhang +13

The Data Science for Pavement Challenge (DSPC) seeks to accelerate the research and development of automated vision systems for pavement condition monitoring and evaluation by prov…

cs.CV2022★ 2 cited

A Region-Based Deep Learning Approach to Automated Retail Checkout

Maged Shoman, Armstrong Aboah, Alex Morehead +3

Automating the product checkout process at conventional retail stores is a task poised to have large impacts on society generally speaking. Towards this end, reliable deep learning…

cs.CV2021

Mobile Sensing for Multipurpose Applications in Transportation

Armstrong Aboah, Michael Boeding, Yaw Adu-Gyamfi

Routine and consistent data collection is required to address contemporary transportation issues.The cost of data collection increases significantly when sophisticated machines are…

cs.CV2021★ 2 cited

A Vision-based System for Traffic Anomaly Detection using Deep Learning and Decision Trees

Armstrong Aboah, Maged Shoman, Vishal Mandal +3

Any intelligent traffic monitoring system must be able to detect anomalies such as traffic accidents in real time. In this paper, we propose a Decision-Tree - enabled approach powe…

cs.CV2020

Deep Learning Frameworks for Pavement Distress Classification: A Comparative Analysis

Vishal Mandal, Abdul Rashid Mussah, Yaw Adu-Gyamfi

Automatic detection and classification of pavement distresses is critical in timely maintaining and rehabilitating pavement surfaces. With the evolution of deep learning and high p…

cs.CV2020

Artificial Intelligence Enabled Traffic Monitoring System

Vishal Mandal, Abdul Rashid Mussah, Peng Jin +1

Manual traffic surveillance can be a daunting task as Traffic Management Centers operate a myriad of cameras installed over a network. Injecting some level of automation could help…

cs.CV2020

Object Detection and Tracking Algorithms for Vehicle Counting: A Comparative Analysis

Vishal Mandal, Yaw Adu-Gyamfi

The rapid advancement in the field of deep learning and high performance computing has highly augmented the scope of video based vehicle counting system. In this paper, the authors…

stat.ML2020★ 292 cited

Deep Machine Learning Approach to Develop a New Asphalt Pavement Condition Index

Hamed Majidifard, Yaw Adu-Gyamfi, William G. Buttlar

Automated pavement distress detection via road images is still a challenging issue among pavement researchers and computer-vision community. In recent years, advancement in deep le…