Search Results for author: Yaw Adu-Gyamfi

Found 18 papers, 1 papers with code

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

no code implementations14 Jan 2024 Linlin Zhang, Xiang Yu, Abdulateef Daud, Abdul Rashid Mussah, Yaw Adu-Gyamfi

This study implements a three-stage video analytics framework for extracting high-resolution traffic data such vehicle counts, speed, and acceleration from infrastructure-mounted CCTV cameras.

Camera Calibration Object Recognition

3D Object Detection and High-Resolution Traffic Parameters Extraction Using Low-Resolution LiDAR Data

no code implementations13 Jan 2024 Linlin Zhang, Xiang Yu, Armstrong Aboah, Yaw Adu-Gyamfi

These are the need for multiple LiDAR systems to obtain complete point cloud information of objects of interest, as well as the labor-intensive process of annotating 3D bounding boxes for object detection tasks.

3D Object Detection object-detection +2

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

no code implementations12 Oct 2023 Neema Jakisa Owor, Hang Du, Abdulateef Daud, Armstrong Aboah, Yaw Adu-Gyamfi

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.


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

no code implementations9 Oct 2023 Abdulateef Daud, Mark Amo-Boateng, Neema Jakisa Owor, Armstrong Aboah, Yaw Adu-Gyamfi

Overall, our proposed device demonstrates significant potential in providing real-time pavement condition data to State Highway Agencies (SHA) and Department of Transportation (DOTs) with a satisfactory level of accuracy.


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

no code implementations13 Apr 2023 Armstrong Aboah, Bin Wang, Ulas Bagci, Yaw Adu-Gyamfi

Real-time implementation of such systems is crucial for traffic surveillance and enforcement, however, most of these systems are not real-time.

object-detection Object Detection

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

no code implementations13 Apr 2023 Armstrong Aboah, Ulas Bagci, Abdul Rashid Mussah, Neema Jakisa Owor, Yaw Adu-Gyamfi

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

Classification Segmentation +1

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

no code implementations23 Jan 2023 Armstrong Aboah, Abdul Rashid Mussah, Yaw Adu-Gyamfi

Furthermore, most studies are restricted to modeling the ego vehicle's acceleration, which is insufficient to explain the behavior of the ego vehicle.

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

no code implementations13 Nov 2022 Maged Shoman, Armstrong Aboah, Abdulateef Daud, Yaw Adu-Gyamfi

Because traffic characteristics display stochastic nonlinear spatiotemporal dependencies, traffic prediction is a challenging task.

Traffic Prediction

Driver Maneuver Detection and Analysis using Time Series Segmentation and Classification

no code implementations10 Nov 2022 Armstrong Aboah, Yaw Adu-Gyamfi, Senem Velipasalar Gursoy, Jennifer Merickel, Matt Rizzo, Anuj Sharma

Previous approaches have treated vehicle maneuver detection as a classification problem, although both time series segmentation and classification are required since input telemetry data is continuous.

Segmentation Time Series +1

The 1st Data Science for Pavements Challenge

no code implementations10 Jun 2022 Ashkan Behzadian, Tanner Wambui Muturi, Tianjie Zhang, Hongmin Kim, Amanda Mullins, Yang Lu, Neema Jasika Owor, Yaw Adu-Gyamfi, William Buttlar, Majidifard Hamed, Armstrong Aboah, David Mensching, Spragg Robert, Matthew Corrigan, Jack Youtchef, Dave Eshan

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 providing a platform with benchmarked datasets and codes for teams to innovate and develop machine learning algorithms that are practice-ready for use by industry.

A Region-Based Deep Learning Approach to Automated Retail Checkout

no code implementations18 Apr 2022 Maged Shoman, Armstrong Aboah, Alex Morehead, Ye Duan, Abdulateef Daud, Yaw Adu-Gyamfi

Automating the product checkout process at conventional retail stores is a task poised to have large impacts on society generally speaking.

object-detection Object Detection

Mobile Sensing for Multipurpose Applications in Transportation

no code implementations20 Jun 2021 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 used to collect data.

Deep Learning Frameworks for Pavement Distress Classification: A Comparative Analysis

1 code implementation21 Oct 2020 Vishal Mandal, Abdul Rashid Mussah, Yaw Adu-Gyamfi

In this study, the authors deploy state-of-the-art deep learning algorithms based on different network backbones to detect and characterize pavement distresses.

Classification General Classification +1

Artificial Intelligence Enabled Traffic Monitoring System

no code implementations2 Oct 2020 Vishal Mandal, Abdul Rashid Mussah, Peng Jin, Yaw Adu-Gyamfi

Real-time object detection algorithms coupled with different tracking systems are deployed to automatically detect stranded vehicles as well as perform vehicular counts.

Management object-detection +1

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

no code implementations31 Jul 2020 Vishal Mandal, Yaw Adu-Gyamfi

In this paper, the authors deploy several state of the art object detection and tracking algorithms to detect and track different classes of vehicles in their regions of interest (ROI).

object-detection Object Detection

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

no code implementations28 Apr 2020 Hamed Majidifard, Yaw Adu-Gyamfi, William G. Buttlar

Afterward, YOLO (you look only once) deep learning framework was implemented to train the model using the labeled dataset.

BIG-bench Machine Learning General Classification

Pavement Image Datasets: A New Benchmark Dataset to Classify and Densify Pavement Distresses

no code implementations20 Oct 2019 Hamed Majidifard, Peng Jin, Yaw Adu-Gyamfi, William G. Buttlar

Automated pavement distresses detection using road images remains a challenging topic in the computer vision research community.

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