764 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University College DublinIE182 papers
- Center for Astrophysics Harvard & SmithsonianUS167 papers
- Purdue University West LafayetteUS154 papers
- McGill UniversityCA153 papers
- University of California, Santa CruzUS151 papers
- Washington University in St. LouisUS150 papers
- Iowa State UniversityUS149 papers
- University of California, Los AngelesUS149 papers
- University of UtahUS149 papers
- Columbia UniversityUS138 papers
- Munster Technological UniversityIE138 papers
- University of ChicagoUS138 papers
31 papers · 1 filter
Learnable Quantum Efficiency Filters for Urban Hyperspectral Segmentation
Imad Ali Shah, Jiarong Li, Ethan Delaney +4
Hyperspectral sensing provides rich spectral information for scene understanding in urban driving, but its high dimensionality poses challenges for interpretation and efficient lea…
A Lightweight 3D-CNN for Event-Based Human Action Recognition with Privacy-Preserving Potential
Mehdi Sefidgar Dilmaghani, Francis Fowley, Peter Corcoran
This paper presents a lightweight three-dimensional convolutional neural network (3DCNN) for human activity recognition (HAR) using event-based vision data. Privacy preservation is…
Hyperspectral Sensors and Autonomous Driving: Technologies, Limitations, and Opportunities
Imad Ali Shah, Jiarong Li, Roshan George +5
Hyperspectral imaging (HSI) offers a transformative sensing modality for Advanced Driver Assistance Systems (ADAS) and autonomous driving (AD) applications, enabling material-level…
Hyperspectral vs. RGB for Pedestrian Segmentation in Urban Driving Scenes: A Comparative Study
Jiarong Li, Imad Ali Shah, Enda Ward +3
Pedestrian segmentation in automotive perception systems faces critical safety challenges due to metamerism in RGB imaging, where pedestrians and backgrounds appear visually indist…
CSNR and JMIM Based Spectral Band Selection for Reducing Metamerism in Urban Driving
Jiarong Li, Imad Ali Shah, Diarmaid Geever +5
Protecting Vulnerable Road Users (VRU) is a critical safety challenge for automotive perception systems, particularly under visual ambiguity caused by metamerism, a phenomenon wher…
YOLOatr : Deep Learning Based Automatic Target Detection and Localization in Thermal Infrared Imagery
Aon Safdar, Usman Akram, Waseem Anwar +2
Automatic Target Detection (ATD) and Recognition (ATR) from Thermal Infrared (TI) imagery in the defense and surveillance domain is a challenging computer vision (CV) task in compa…
Sampling Matters in Explanations: Towards Trustworthy Attribution Analysis Building Block in Visual Models through Maximizing Explanation Certainty
Róisín Luo, James McDermott, Colm O'Riordan
Image attribution analysis seeks to highlight the feature representations learned by visual models such that the highlighted feature maps can reflect the pixel-wise importance of i…
Hyperspectral Imaging-Based Perception in Autonomous Driving Scenarios: Benchmarking Baseline Semantic Segmentation Models
Imad Ali Shah, Jiarong Li, Martin Glavin +3
Hyperspectral Imaging (HSI) is known for its advantages over traditional RGB imaging in remote sensing, agriculture, and medicine. Recently, it has gained attention for enhancing A…
Depth Estimation using Weighted-loss and Transfer Learning
Muhammad Adeel Hafeez, Michael G. Madden, Ganesh Sistu +1
Depth estimation from 2D images is a common computer vision task that has applications in many fields including autonomous vehicles, scene understanding and robotics. The accuracy…
Surround-View Fisheye Optics in Computer Vision and Simulation: Survey and Challenges
Daniel Jakab, Brian Michael Deegan, Sushil Sharma +6
In this paper, we provide a survey on automotive surround-view fisheye optics, with an emphasis on the impact of optical artifacts on computer vision tasks in autonomous driving an…
Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN
Muhammad Ali Farooq, Wang Yao, Michael Schukat +2
This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusion models as a strategy for enhancing the robustness of machine learning model t…
ChildGAN: Large Scale Synthetic Child Facial Data Using Domain Adaptation in StyleGAN
Muhammad Ali Farooq, Wang Yao, Gabriel Costache +1
In this research work, we proposed a novel ChildGAN, a pair of GAN networks for generating synthetic boys and girls facial data derived from StyleGAN2. ChildGAN is built by perform…
Meme Sentiment Analysis Enhanced with Multimodal Spatial Encoding and Facial Embedding
Muzhaffar Hazman, Susan McKeever, Josephine Griffith
Internet memes are characterised by the interspersing of text amongst visual elements. State-of-the-art multimodal meme classifiers do not account for the relative positions of the…
Recurrent Super-Resolution Method for Enhancing Low Quality Thermal Facial Data
David O'Callaghan, Cian Ryan, Waseem Shariff +3
The process of obtaining high-resolution images from single or multiple low-resolution images of the same scene is of great interest for real-world image and signal processing appl…
E-Scooter Rider Detection and Classification in Dense Urban Environments
Shane Gilroy, Darragh Mullins, Edward Jones +2
Accurate detection and classification of vulnerable road users is a safety critical requirement for the deployment of autonomous vehicles in heterogeneous traffic. Although similar…
The Impact of Partial Occlusion on Pedestrian Detectability
Shane Gilroy, Darragh Mullins, Edward Jones +2
Robust detection of vulnerable road users is a safety critical requirement for the deployment of autonomous vehicles in heterogeneous traffic. One of the most complex outstanding c…
Evaluation of Thermal Imaging on Embedded GPU Platforms for Application in Vehicular Assistance Systems
Muhammad Ali Farooq, Waseem Shariff, Peter Corcoran
This study is focused on evaluating the real-time performance of thermal object detection for smart and safe vehicular systems by deploying the trained networks on GPU & single-boa…
Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment
Muhammad Ali Farooq, Ammar Ali Khan, Ansar Ahmad +1
Image Super Resolution (SR) finds applications in areas where images need to be closely inspected by the observer to extract enhanced information. One such focused application is a…
VID-WIN: Fast Video Event Matching with Query-Aware Windowing at the Edge for the Internet of Multimedia Things
Piyush Yadav, Dhaval Salwala, Edward Curry
Efficient video processing is a critical component in many IoMT applications to detect events of interest. Presently, many window optimization techniques have been proposed in even…
A Multi-class Approach -- Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning
Preeti Jagdish Sajjan, Frank G. Glavin
Machine Learning (ML) techniques for image classification routinely require many labelled images for training the model and while testing, we ought to use images belonging to the s…
VidCEP: Complex Event Processing Framework to Detect Spatiotemporal Patterns in Video Streams
Piyush Yadav, Edward Curry
Video data is highly expressive and has traditionally been very difficult for a machine to interpret. Querying event patterns from video streams is challenging due to its unstructu…
Traffic Prediction Framework for OpenStreetMap using Deep Learning based Complex Event Processing and Open Traffic Cameras
Piyush Yadav, Dipto Sarkar, Dhaval Salwala +1
Displaying near-real-time traffic information is a useful feature of digital navigation maps. However, most commercial providers rely on privacy-compromising measures such as deriv…
Generating Thermal Image Data Samples using 3D Facial Modelling Techniques and Deep Learning Methodologies
Muhammad Ali Farooq, Peter Corcoran
Methods for generating synthetic data have become of increasing importance to build large datasets required for Convolution Neural Networks (CNN) based deep learning techniques for…
Dataset Cleaning -- A Cross Validation Methodology for Large Facial Datasets using Face Recognition
Viktor Varkarakis, Peter Corcoran
In recent years, large "in the wild" face datasets have been released in an attempt to facilitate progress in tasks such as face detection, face recognition, and other tasks. Most…