Samuel Bilson
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View article: Uncertainty-aware Bayesian machine learning modelling of land cover classification
Uncertainty-aware Bayesian machine learning modelling of land cover classification Open
Land cover classification involves the production of land cover maps, which determine the type of land through remote sensing imagery. Over recent years, such classification is being performed by machine learning classification models, whi…
View article: A machine learning approach to automation and uncertainty evaluation for self-validating thermocouples
A machine learning approach to automation and uncertainty evaluation for self-validating thermocouples Open
Thermocouples are in widespread use in industry, but they are particularly susceptible to calibration drift in harsh environments. Self-validating thermocouples aim to address this issue by using a miniature phase-change cell (fixed-point)…
View article: Physics-Informed Machine Learning Modelling of RF-EMF Exposure in Massive MIMO Systems
Physics-Informed Machine Learning Modelling of RF-EMF Exposure in Massive MIMO Systems Open
Beamforming and massive multiple-input-multiple-output (mMIMO) technologies are key features of base stations (BSs) in the fifth-generation (5G) of mobile networks. This technology is used to focus more radio frequency (RF) energy towards …
View article: A review of applications of supervised learning to future networks
A review of applications of supervised learning to future networks Open
Automatic modulation classification ASE Amplified spontaneous emission BER Bit error rate BLER Block error rate CD Chromatic dispersion CNN Convolutional neural network C-RAN Centralised radio access network CSI Channel state information D…
View article: Bayesian uncertainty quantification for transmissibility of influenza, norovirus and Ebola using information geometry
Bayesian uncertainty quantification for transmissibility of influenza, norovirus and Ebola using information geometry Open
Infectious diseases exert a large and in many contexts growing burden on human health, but violate most of the assumptions of classical epidemiological statistics and hence require a mathematically sophisticated approach. Viral shedding da…