Sensing moisture patterns using terahertz spectroscopy

M. Koumans; A. Pérez-Casanova; J.L.M. van Mechelen

doi:10.1109/IRMMW-THz50927.2022.9895781

Sensing moisture patterns using terahertz spectroscopy

M. Koumans, A. Pérez-Casanova, J.L.M. van Mechelen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

2 Downloads (Pure)

Abstract

We report on a novel and comprehensive method to determine leaf wetness by using machine learning algorithms applied on transmission THz time-domain data of a vast set of moisture patterns. More generally, our approach opens ways to determine properties of materials with a complex structure for which a model-based signal processing approach is not feasible.

Original language	English
Title of host publication	IRMMW-THz 2022 - 47th International Conference on Infrared, Millimeter and Terahertz Waves
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	2
ISBN (Electronic)	9781728194271
DOIs	https://doi.org/10.1109/IRMMW-THz50927.2022.9895781
Publication status	Published - 26 Sept 2022
Event	47th International Conference on Infrared, Millimeter and Terahertz Waves, IRMMW-THz 2022 - Technical University Delft, Delft, Netherlands Duration: 28 Aug 2022 → 2 Sept 2022 Conference number: 47 https://www.irmmw-thz2022.tudelft.nl/

Conference

Conference	47th International Conference on Infrared, Millimeter and Terahertz Waves, IRMMW-THz 2022
Abbreviated title	IRMMW-THz
Country/Territory	Netherlands
City	Delft
Period	28/08/22 → 2/09/22
Internet address	https://www.irmmw-thz2022.tudelft.nl/

Access to Document

10.1109/IRMMW-THz50927.2022.9895781

Cite this

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title = "Sensing moisture patterns using terahertz spectroscopy",

abstract = "We report on a novel and comprehensive method to determine leaf wetness by using machine learning algorithms applied on transmission THz time-domain data of a vast set of moisture patterns. More generally, our approach opens ways to determine properties of materials with a complex structure for which a model-based signal processing approach is not feasible.",

author = "M. Koumans and A. P{\'e}rez-Casanova and \{van Mechelen\}, J.L.M.",

year = "2022",

month = sep,

day = "26",

doi = "10.1109/IRMMW-THz50927.2022.9895781",

language = "English",

booktitle = "IRMMW-THz 2022 - 47th International Conference on Infrared, Millimeter and Terahertz Waves",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "47th International Conference on Infrared, Millimeter and Terahertz Waves, IRMMW-THz 2022, IRMMW-THz ; Conference date: 28-08-2022 Through 02-09-2022",

url = "https://www.irmmw-thz2022.tudelft.nl/",

}

Koumans, M, Pérez-Casanova, A & van Mechelen, JLM 2022, Sensing moisture patterns using terahertz spectroscopy. in IRMMW-THz 2022 - 47th International Conference on Infrared, Millimeter and Terahertz Waves., 9895781, Institute of Electrical and Electronics Engineers, 47th International Conference on Infrared, Millimeter and Terahertz Waves, IRMMW-THz 2022, Delft, Netherlands, 28/08/22. https://doi.org/10.1109/IRMMW-THz50927.2022.9895781

Sensing moisture patterns using terahertz spectroscopy. / Koumans, M.; Pérez-Casanova, A.; van Mechelen, J.L.M.
IRMMW-THz 2022 - 47th International Conference on Infrared, Millimeter and Terahertz Waves. Institute of Electrical and Electronics Engineers, 2022. 9895781.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Sensing moisture patterns using terahertz spectroscopy

AU - Koumans, M.

AU - Pérez-Casanova, A.

AU - van Mechelen, J.L.M.

N1 - Conference code: 47

PY - 2022/9/26

Y1 - 2022/9/26

N2 - We report on a novel and comprehensive method to determine leaf wetness by using machine learning algorithms applied on transmission THz time-domain data of a vast set of moisture patterns. More generally, our approach opens ways to determine properties of materials with a complex structure for which a model-based signal processing approach is not feasible.

AB - We report on a novel and comprehensive method to determine leaf wetness by using machine learning algorithms applied on transmission THz time-domain data of a vast set of moisture patterns. More generally, our approach opens ways to determine properties of materials with a complex structure for which a model-based signal processing approach is not feasible.

UR - https://www.scopus.com/pages/publications/85139821746

U2 - 10.1109/IRMMW-THz50927.2022.9895781

DO - 10.1109/IRMMW-THz50927.2022.9895781

M3 - Conference contribution

AN - SCOPUS:85139821746

BT - IRMMW-THz 2022 - 47th International Conference on Infrared, Millimeter and Terahertz Waves

PB - Institute of Electrical and Electronics Engineers

T2 - 47th International Conference on Infrared, Millimeter and Terahertz Waves, IRMMW-THz 2022

Y2 - 28 August 2022 through 2 September 2022

ER -

Sensing moisture patterns using terahertz spectroscopy

Abstract

Conference

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