6 citations · 8 across the 7 of their papers we have counts for
3 papers · 1 filter
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…
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…
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations
Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez +5
In supervised learning, low quality annotations lead to poorly performing classification and detection models, while also rendering evaluation unreliable. This is particularly appa…