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cs.LG2024
Transfer Learning of RSSI to Improve Indoor Localisation Performance
Thanaphon Suwannaphong, Ryan McConville, Ian Craddock
With the growing demand for health monitoring systems, in-home localisation is essential for tracking patient conditions. The unique spatial characteristics of each house required…
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…