334 citations · 1.3k across the 54 of their papers we have counts for
63 papers
Breathing Green: Maximising Health and Environmental Benefits for Active Transportation Users Leveraging Large Scale Air Quality Data
Sen Yan, Shaoshu Zhu, Jaime B. Fernandez +5
Pollution in urban areas can have significant adverse effects on the health and well-being of citizens, with traffic-related air pollution being a major concern in many cities. Pol…
Fashion CUT: Unsupervised domain adaptation for visual pattern classification in clothes using synthetic data and pseudo-labels
Enric Moreu, Alex Martinelli, Martina Naughton +2
Accurate product information is critical for e-commerce stores to allow customers to browse, filter, and search for products. Product data quality is affected by missing or incorre…
U-Park: A User-Centric Smart Parking Recommendation System for Electric Shared Micromobility Services
Sen Yan, Noel E. O'Connor, Mingming Liu
Electric Shared Micromobility Services (ESMS) has become a vital element within the Mobility as a Service framework, contributing to sustainable transportation systems. However, ex…
Embedding contrastive unsupervised features to cluster in- and out-of-distribution noise in corrupted image datasets
Paul Albert, Eric Arazo, Noel E. O'Connor +1
Using search engines for web image retrieval is a tempting alternative to manual curation when creating an image dataset, but their main drawback remains the proportion of incorrec…
Dynamic Channel Selection in Self-Supervised Learning
Tarun Krishna, Ayush K. Rai, Yasser A. D. Djilali +3
Whilst computer vision models built using self-supervised approaches are now commonplace, some important questions remain. Do self-supervised models learn highly redundant channel…
Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation
Paul Albert, Mohamed Saadeldin, Badri Narayanan +5
Sward species composition estimation is a tedious one. Herbage must be collected in the field, manually separated into components, dried and weighed to estimate species composition…
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation
Paul Albert, Mohamed Saadeldin, Badri Narayanan +5
Herbage mass yield and composition estimation is an important tool for dairy farmers to ensure an adequate supply of high quality herbage for grazing and subsequently milk producti…
Parking Behaviour Analysis of Shared E-Bike Users Based on a Real-World Dataset -- A Case Study in Dublin, Ireland
Sen Yan, Mingming Liu, Noel E. O'Connor
In recent years, an increasing number of shared E-bikes have been rolling out rapidly in our cities. It therefore becomes important to understand new behaviour patterns of the cycl…
Synthetic data for unsupervised polyp segmentation
Enric Moreu, Kevin McGuinness, Noel E. O'Connor
Deep learning has shown excellent performance in analysing medical images. However, datasets are difficult to obtain due privacy issues, standardization problems, and lack of annot…
Domain Randomization for Object Counting
Enric Moreu, Kevin McGuinness, Diego Ortego +1
Recently, the use of synthetic datasets based on game engines has been shown to improve the performance of several tasks in computer vision. However, these datasets are typically o…
BERTHA: Video Captioning Evaluation Via Transfer-Learned Human Assessment
Luis Lebron, Yvette Graham, Kevin McGuinness +2
Evaluating video captioning systems is a challenging task as there are multiple factors to consider; for instance: the fluency of the caption, multiple actions happening in a singl…
Improving Person Re-Identification with Temporal Constraints
Julia Dietlmeier, Feiyan Hu, Frances Ryan +2
In this paper we introduce an image-based person re-identification dataset collected across five non-overlapping camera views in the large and busy airport in Dublin, Ireland. Unli…
How Important is Importance Sampling for Deep Budgeted Training?
Eric Arazo, Diego Ortego, Paul Albert +2
Long iterative training processes for Deep Neural Networks (DNNs) are commonly required to achieve state-of-the-art performance in many computer vision tasks. Importance sampling a…
Semi-supervised dry herbage mass estimation using automatic data and synthetic images
Paul Albert, Mohamed Saadeldin, Badri Narayanan +5
Monitoring species-specific dry herbage biomass is an important aspect of pasture-based milk production systems. Being aware of the herbage biomass in the field enables farmers to…
Addressing out-of-distribution label noise in webly-labelled data
Paul Albert, Diego Ortego, Eric Arazo +2
A recurring focus of the deep learning community is towards reducing the labeling effort. Data gathering and annotation using a search engine is a simple alternative to generating…
Solving the Real Robot Challenge using Deep Reinforcement Learning
Robert McCarthy, Francisco Roldan Sanchez, Qiang Wang +4
This paper details our winning submission to Phase 1 of the 2021 Real Robot Challenge; a challenge in which a three-fingered robot must carry a cube along specified goal trajectori…
Real Robot Challenge: A Robotics Competition in the Cloud
Stefan Bauer, Felix Widmaier, Manuel Wüthrich +39
Dexterous manipulation remains an open problem in robotics. To coordinate efforts of the research community towards tackling this problem, we propose a shared benchmark. We designe…
Discerning Generic Event Boundaries in Long-Form Wild Videos
Ayush K Rai, Tarun Krishna, Julia Dietlmeier +3
Detecting generic, taxonomy-free event boundaries invideos represents a major stride forward towards holisticvideo understanding. In this paper we present a technique forgeneric ev…
Attention-based Stylisation for Exemplar Image Colourisation
Marc Gorriz Blanch, Issa Khalifeh, Alan Smeaton +2
Exemplar-based colourisation aims to add plausible colours to a grayscale image using the guidance of a colour reference image. Most of the existing methods tackle the task as a st…
Optimal Distributed Bandwidth Allocation in NB-IoT Networks
Hongde Wu, Zhengyong Chen, Noel E. O'Connor +1
In this paper, we investigate a key problem of Narrowband-Internet of Things (NB-IoT) in the context of 5G with Mobile Edge Computing (MEC). We address the challenge that IoT devic…
Evaluating Contrastive Models for Instance-based Image Retrieval
Tarun Krishna, Kevin McGuinness, Noel O'Connor
In this work, we evaluate contrastive models for the task of image retrieval. We hypothesise that models that are learned to encode semantic similarity among instances via discrimi…
An ADMM-based Optimal Transmission Frequency Management System for IoT Edge Intelligence
Hongde Wu, Noel E. O'Connor, Jennifer Bruton +1
In this paper, we investigate a key problem of Internet of Things (IoT) applications in practice. Our research objective is to optimize the transmission frequencies for a group of…
A Comparative Study of Using Spatial-Temporal Graph Convolutional Networks for Predicting Availability in Bike Sharing Schemes
Zhengyong Chen, Hongde Wu, Noel E. O'Connor +1
Accurately forecasting transportation demand is crucial for efficient urban traffic guidance, control and management. One solution to enhance the level of prediction accuracy is to…
An Intelligent Multi-Speed Advisory System using Improved Whale Optimisation Algorithm
Beiran Chen, Mingming Liu, Yi Zhang +3
An intelligent speed advisory system can be used to recommend speed for vehicles travelling in a given road network in cities. In this paper, we extend our previous work where a di…