Browsing by Author "Jakobsen, Mogens H."

Browsing by Author "Jakobsen, Mogens H."

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  • Classification of colorimetric sensor data using time series 
    Francis, Deena P.; Laustsen, Milan; Babamoradi, Hamid; Mogensen, Jesper; Dossi, Eleftheria; Jakobsen, Mogens H.; Alstrøm, Tommy S. (Society of Photo-Optical Instrumentation Engineers (SPIE), 2021-09-12)
    Colorimetric sensors are widely used as pH indicators, medical diagnostic devices and detection devices. The colorimetric sensor captures the color changes of a chromic chemical (dye) or array of chromic chemicals when ...
  • CRIM-TRACK: Sensor system for detection of criminal chemical substances 
    Munk, Jens Kristian; Buus, Ole T.; Larsen, Jan; Dossi, Eleftheria; Tatlow, Sol; Lässig, Lina; Sandström, Lars; Jakobsen, Mogens H. (SPIE, 2015-10-21)
    Detection of illegal compounds requires a reliable, selective and sensitive detection device. The successful device features automated target acquisition, identification and signal processing. It is portable, fast, user ...
  • Improved detection of chemical substances from colorimetric sensor data using probabilistic machine learning 
    Mølgaard, Lasse L.; Buus, Ole T.; Larsen, Jan; Babamoradi, Hamid; Thygesen, Ida L.; Laustsen, Milan; Munk, Jens Kristian; Dossi, Eleftheria; O'Keeffe, Caroline; Lässig, Lina; Tatlow, Sol; Sandström, Lars; Jakobsen, Mogens H. (SPIE, 2017-05)
    We present a data-driven machine learning approach to detect drug- and explosives-precursors using colorimetric sensor technology for air-sampling. The sensing technology has been developed in the context of the CRIM-TRACK ...
  • Machine learning methods for the detection of explosives, drugs and precursor chemicals gathered using a colorimetric sniffer sensor 
    Francis, Deena P.; Laustsen, Milan; Dossi, Eleftheria; Treiberg, Tuule; Hardy, Iona; Shiv, Shai Hvid; Hansen, Bo Svarrer; Mogensen, Jesper; Jakobsen, Mogens H.; Alstrøm, Tommy S. (Royal Society of Chemistry, 2023-04-18)
    Colorimetric sensing technology for the detection of explosives, drugs, and their precursor chemicals is an important and effective approach. In this work, we use various machine learning models to detect these substances ...