169 citations · 367 across the 10 of their papers we have counts for
10 papers
Enhancing Fast Radio Transient Detection with Mask R-CNN Image Segmentation
Sergio Belmonte Diaz, Rene P. Breton, Zafiirah Hosenie +1
Traditionally, fast radio transient searches are conducted on dedispersed time series using thresholding techniques based on the statistical properties of the data. However, peaks…
VoluMe -- Authentic 3D Video Calls from Live Gaussian Splat Prediction
Martin de La Gorce, Charlie Hewitt, Tibor Takacs +6
Virtual 3D meetings offer the potential to enhance copresence, increase engagement and thus improve effectiveness of remote meetings compared to standard 2D video calls. However, r…
Hairmony: Fairness-aware hairstyle classification
Givi Meishvili, James Clemoes, Charlie Hewitt +9
We present a method for prediction of a person's hairstyle from a single image. Despite growing use cases in user digitization and enrollment for virtual experiences, available met…
Look Ma, no markers: holistic performance capture without the hassle
Charlie Hewitt, Fatemeh Saleh, Sadegh Aliakbarian +8
We tackle the problem of highly-accurate, holistic performance capture for the face, body and hands simultaneously. Motion-capture technologies used in film and game production typ…
MeerCRAB: MeerLICHT Classification of Real and Bogus Transients using Deep Learning
Zafiirah Hosenie, Steven Bloemen, Paul Groot +13
Astronomers require efficient automated detection and classification pipelines when conducting large-scale surveys of the (optical) sky for variable and transient sources. Such pip…
Imbalance Learning for Variable Star Classification
Zafiirah Hosenie, Robert Lyon, Benjamin Stappers +2
The accurate automated classification of variable stars into their respective sub-types is difficult. Machine learning based solutions often fall foul of the imbalanced learning pr…
Comparing Multi-class, Binary and Hierarchical Machine Learning Classification schemes for variable stars
Zafiirah Hosenie, Robert Lyon, Benjamin Stappers +1
Upcoming synoptic surveys are set to generate an unprecedented amount of data. This requires an automatic framework that can quickly and efficiently provide classification labels f…
DeepSource: Point Source Detection using Deep Learning
A. Vafaei Sadr, Etienne. E. Vos, Bruce A. Bassett +3
Point source detection at low signal-to-noise is challenging for astronomical surveys, particularly in radio interferometry images where the noise is correlated. Machine learning i…
Marginal Likelihoods from Monte Carlo Markov Chains
Alan Heavens, Yabebal Fantaye, Arrykrishna Mootoovaloo +4
In this paper, we present a method for computing the marginal likelihood, also known as the model likelihood or Bayesian evidence, from Markov Chain Monte Carlo (MCMC), or other sa…
No evidence for extensions to the standard cosmological model
Alan Heavens, Yabebal Fantaye, Elena Sellentin +4
We compute the Bayesian Evidence for models considered in the main analysis of Planck cosmic microwave background data. By utilising carefully-defined nearest-neighbour distances i…