• Blind Calibration of Air Quality Wireless Sensor Networks Using Deep Neural Networks 

      Veiga, Tiago Santos; Ljunggren, Erling; Bach, Kerstin; Akselsen, Sigmund (Chapter, 2021)
      Temporal drift of low-cost sensors is crucial for the applicability of wireless sensor networks (WSN) to measure highly local phenomenon such as air quality. The emergence of wireless sensor networks in locations without ...
    • Deep Learning for Blind Calibration of Wireless Sensor Networks 

      Ljunggren, Erling (Master thesis, 2020)
      Temporal drift of low-cost sensors is a crucial problem when considering the applicability of wireless sensor networks (WSN). Since they provide highly local measurements, which is key to combat the ever increasing problem ...