20 citations · 30 across the 6 of their papers we have counts for
6 papers
Transformer-Based Source Detection and Morphological Classification in LOFAR Deep-Field Continuum Images
Guangwen Chen, Kristian Z. Adami, John Abela +7
Radio source detection and morphological classification are fundamental for exploiting the scientific potential of modern radio continuum surveys. However, the rapidly increasing d…
The Best of Both Worlds: a Framework for Combining Degradation Prediction with High Performance Super-Resolution Networks
Matthew Aquilina, Keith George Ciantar, Christian Galea +3
To date, the best-performing blind super-resolution (SR) techniques follow one of two paradigms: A) generate and train a standard SR network on synthetic low-resolution - high-reso…
Improving Super-Resolution Performance using Meta-Attention Layers
Matthew Aquilina, Christian Galea, John Abela +2
Convolutional Neural Networks (CNNs) have achieved impressive results across many super-resolution (SR) and image restoration tasks. While many such networks can upscale low-resolu…
Optimal SKA Dish Configuration using Genetic Algorithms
Adam Gauci, Kristian Zarb Adami, John Abela +1
The Square Kilometre Array (SKA) is a radio telescope designed to operate between 70MHz and 10GHz. Due to this large bandwidth, the SKA will be built out of different collectors, n…
Gravitational wave detection and cosmic string detection with current radio interferometers
Kristian Zarb Adami, Adam Gauci, John Abela
The authors apologise for the preliminary submission of this paper.
Machine Learning for Galaxy Morphology Classification
Adam Gauci, Kristian Zarb Adami, John Abela
In this work, decision tree learning algorithms and fuzzy inferencing systems are applied for galaxy morphology classification. In particular, the CART, the C4.5, the Random Forest…