2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2022
Modelling calibration uncertainty in networks of environmental sensors
Michael Thomas Smith, Magnus Ross, Joel Ssematimba +4
Networks of low-cost sensors are becoming ubiquitous, but often suffer from poor accuracies and drift. Regular colocation with reference sensors allows recalibration but is complic…
cs.LG2019★ 2 cited
Machine Learning for a Low-cost Air Pollution Network
Michael T. Smith, Joel Ssematimba, Mauricio A. Alvarez +1
Data collection in economically constrained countries often necessitates using approximate and biased measurements due to the low-cost of the sensors used. This leads to potentiall…