6 citations · 10 across the 6 of their papers we have counts for
6 papers
Exploring the Unexplored: Understanding the Impact of Layer Adjustments on Image Classification
Haixia Liu, Tim Brailsford, James Goulding +2
This paper investigates how adjustments to deep learning architectures impact model performance in image classification. Small-scale experiments generate initial insights although…
CCC/Code 8.7: Applying AI in the Fight Against Modern Slavery
Nadya Bliss, Mark Briers, Alice Eckstein +4
On any given day, tens of millions of people find themselves trapped in instances of modern slavery. The terms "human trafficking," "trafficking in persons," and "modern slavery" a…
The Bayesian Spatial Bradley--Terry Model: Urban Deprivation Modeling in Tanzania
R. G. Seymour, D. Sirl, S. Preston +4
Identifying the most deprived regions of any country or city is key if policy makers are to design successful interventions. However, locating areas with the greatest need is often…
On Bayesian inferential tasks with infinite-state jump processes: efficient data augmentation
Iker Perez, Lax Chan, Mercedes Torres Torres +2
Advances in sampling schemes for Markov jump processes have recently enabled multiple inferential tasks. However, in statistical and machine learning applications, we often require…
Classification and clustering for observations of event time data using non-homogeneous Poisson process models
Duncan Barrack, Simon Preston
Data of the form of event times arise in various applications. A simple model for such data is a non-homogeneous Poisson process (NHPP) which is specified by a rate function that d…
AMP: a new time-frequency feature extraction method for intermittent time-series data
Duncan Barrack, James Goulding, Keith Hopcraft +2
The characterisation of time-series data via their most salient features is extremely important in a range of machine learning task, not least of all with regards to classification…