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cs.LG2024
Optimising TinyML with Quantization and Distillation of Transformer and Mamba Models for Indoor Localisation on Edge Devices
Thanaphon Suwannaphong, Ferdian Jovan, Ian Craddock +1
This paper proposes small and efficient machine learning models (TinyML) for resource-constrained edge devices, specifically for on-device indoor localisation. Typical approaches f…
cs.LG2022
Multimodal Indoor Localisation for Measuring Mobility in Parkinson's Disease using Transformers
Ferdian Jovan, Ryan McConville, Catherine Morgan +3
Parkinson's disease (PD) is a slowly progressive debilitating neurodegenerative disease which is prominently characterised by motor symptoms. Indoor localisation, including number…