6 papers
Integrating Semi-Supervised and Active Learning for Semantic Segmentation
Wanli Ma, Oktay Karakus, Paul L. Rosin
In this paper, we propose a novel active learning approach integrated with an improved semi-supervised learning framework to reduce the cost of manual annotation and enhance model…
A Multi-Modal Spatial Risk Framework for EV Charging Infrastructure Using Remote Sensing
Oktay KarakuÅ, Padraig Corcoran
Electric vehicle (EV) charging infrastructure is increasingly critical to sustainable transport systems, yet its resilience under environmental and infrastructural stress remains u…
DiverseNet: Decision Diversified Semi-supervised Semantic Segmentation Networks for Remote Sensing Imagery
Wanli Ma, Oktay Karakus, Paul L. Rosin
Semi-supervised learning (SSL) aims to help reduce the cost of the manual labelling process by leveraging a substantial pool of unlabelled data alongside a limited set of labelled…
Multi-modal Data Fusion and Deep Ensemble Learning for Accurate Crop Yield Prediction
Akshay Dagadu Yewle, Laman Mirzayeva, Oktay KarakuÅ
This study introduces RicEns-Net, a novel Deep Ensemble model designed to predict crop yields by integrating diverse data sources through multimodal data fusion techniques. The res…
Patch-GAN Transfer Learning with Reconstructive Models for Cloud Removal
Wanli Ma, Oktay Karakus, Paul L. Rosin
Cloud removal plays a crucial role in enhancing remote sensing image analysis, yet accurately reconstructing cloud-obscured regions remains a significant challenge. Recent advancem…
Quantifying Extreme Opinions on Reddit Amidst the 2023 Israeli-Palestinian Conflict
Alessio Guerra, Marcello Lepre, Oktay Karakus
This study investigates the dynamics of extreme opinions on social media during the 2023 Israeli-Palestinian conflict, utilising a comprehensive dataset of over 450,000 posts from…