118 citations · 216 across the 30 of their papers we have counts for
8 papers · 1 filter
Tabular Machine Learning Methods for Predicting Gas Turbine Emissions
Rebecca Potts, Rick Hackney, Georgios Leontidis
Predicting emissions for gas turbines is critical for monitoring harmful pollutants being released into the atmosphere. In this study, we evaluate the performance of machine learni…
ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method
Miles Everett, Mingjun Zhong, Georgios Leontidis
Capsule Networks have emerged as a powerful class of deep learning architectures, known for robust performance with relatively few parameters compared to Convolutional Neural Netwo…
Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination Methods
Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong
Self-supervised learning algorithms (SSL) based on instance discrimination have shown promising results, performing competitively or even outperforming supervised learning counterp…
HMSN: Hyperbolic Self-Supervised Learning by Clustering with Ideal Prototypes
Aiden Durrant, Georgios Leontidis
Hyperbolic manifolds for visual representation learning allow for effective learning of semantic class hierarchies by naturally embedding tree-like structures with low distortion w…
Vanishing Activations: A Symptom of Deep Capsule Networks
Miles Everett, Mingjun Zhong, Georgios Leontidis
Capsule Networks, an extension to Neural Networks utilizing vector or matrix representations instead of scalars, were initially developed to create a dynamic parse tree where visua…
S-JEA: Stacked Joint Embedding Architectures for Self-Supervised Visual Representation Learning
Alžběta Manová, Aiden Durrant, Georgios Leontidis
The recent emergence of Self-Supervised Learning (SSL) as a fundamental paradigm for learning image representations has, and continues to, demonstrate high empirical success in a v…
Model Pruning Enables Localized and Efficient Federated Learning for Yield Forecasting and Data Sharing
Andy Li, Milan Markovic, Peter Edwards +1
Federated Learning (FL) presents a decentralized approach to model training in the agri-food sector and offers the potential for improved machine learning performance, while ensuri…
Deep learning universal crater detection using Segment Anything Model (SAM)
Iraklis Giannakis, Anshuman Bhardwaj, Lydia Sam +1
Craters are amongst the most important morphological features in planetary exploration. To that extent, detecting, mapping and counting craters is a mainstream process in planetary…