---
_id: '11978'
author:
- first_name: Arthur
full_name: Gossen, Arthur
id: '76446'
last_name: Gossen
- first_name: Linda
full_name: Katsch, Linda
id: '71614'
last_name: Katsch
orcid: '0000-0001-6628-3929 '
- first_name: Mandy Isabel
full_name: Meyer, Mandy Isabel
id: '71991'
last_name: Meyer
- first_name: Manuel
full_name: Zimmer, Manuel
id: '71613'
last_name: Zimmer
orcid: 0000-0002-9974-2543
- first_name: Martyna
full_name: Bator, Martyna
id: '46440'
last_name: Bator
- first_name: Masoumeh
full_name: Darvishi, Masoumeh
id: '81495'
last_name: Darvishi
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
- first_name: Jan
full_name: Schneider, Jan
id: '13209'
last_name: Schneider
orcid: 0000-0001-6401-8873
citation:
ama: 'Gossen A, Katsch L, Meyer MI, et al. FoodLifeTimeTracking: Datengetriebene
Dynamische Haltbarkeitsvorhersage von Erfrischungsgetränken.; 2024.'
apa: 'Gossen, A., Katsch, L., Meyer, M. I., Zimmer, M., Bator, M., Darvishi, M.,
Holst, C.-A., Lohweg, V., & Schneider, J. (2024). FoodLifeTimeTracking:
Datengetriebene dynamische Haltbarkeitsvorhersage von Erfrischungsgetränken.
GDL Kongress Lebensmitteltechnologie, Lemgo.'
bjps: 'Gossen A et al. (2024) FoodLifeTimeTracking: Datengetriebene
Dynamische Haltbarkeitsvorhersage von Erfrischungsgetränken. .'
chicago: 'Gossen, Arthur, Linda Katsch, Mandy Isabel Meyer, Manuel Zimmer, Martyna
Bator, Masoumeh Darvishi, Christoph-Alexander Holst, Volker Lohweg, and Jan Schneider.
FoodLifeTimeTracking: Datengetriebene Dynamische Haltbarkeitsvorhersage von
Erfrischungsgetränken, 2024.'
chicago-de: 'Gossen, Arthur, Linda Katsch, Mandy Isabel Meyer, Manuel Zimmer, Martyna
Bator, Masoumeh Darvishi, Christoph-Alexander Holst, Volker Lohweg und Jan Schneider.
2024. FoodLifeTimeTracking: Datengetriebene dynamische Haltbarkeitsvorhersage
von Erfrischungsgetränken.'
din1505-2-1: 'Gossen,
Arthur ; Katsch, Linda ;
Meyer, Mandy Isabel ; Zimmer,
Manuel ; Bator, Martyna ;
Darvishi, Masoumeh ; Holst,
Christoph-Alexander ; Lohweg, Volker
; u. a.: FoodLifeTimeTracking: Datengetriebene dynamische Haltbarkeitsvorhersage
von Erfrischungsgetränken, 2024'
havard: 'A. Gossen, L. Katsch, M.I. Meyer, M. Zimmer, M. Bator, M. Darvishi, C.-A.
Holst, V. Lohweg, J. Schneider, FoodLifeTimeTracking: Datengetriebene dynamische
Haltbarkeitsvorhersage von Erfrischungsgetränken, 2024.'
ieee: 'A. Gossen et al., FoodLifeTimeTracking: Datengetriebene dynamische
Haltbarkeitsvorhersage von Erfrischungsgetränken. 2024.'
mla: 'Gossen, Arthur, et al. FoodLifeTimeTracking: Datengetriebene Dynamische
Haltbarkeitsvorhersage von Erfrischungsgetränken. 2024.'
short: 'A. Gossen, L. Katsch, M.I. Meyer, M. Zimmer, M. Bator, M. Darvishi, C.-A.
Holst, V. Lohweg, J. Schneider, FoodLifeTimeTracking: Datengetriebene Dynamische
Haltbarkeitsvorhersage von Erfrischungsgetränken, 2024.'
ufg: 'Gossen, Arthur u. a.: FoodLifeTimeTracking: Datengetriebene dynamische
Haltbarkeitsvorhersage von Erfrischungsgetränken, o. O. 2024.'
van: 'Gossen A, Katsch L, Meyer MI, Zimmer M, Bator M, Darvishi M, et al. FoodLifeTimeTracking:
Datengetriebene dynamische Haltbarkeitsvorhersage von Erfrischungsgetränken. 2024.'
conference:
end_date: 2024-10-12
location: Lemgo
name: GDL Kongress Lebensmitteltechnologie
start_date: 2024-10-10
date_created: 2024-10-09T14:17:04Z
date_updated: 2025-10-17T18:30:10Z
department:
- _id: DEP4018
- _id: DEP5023
- _id: DEP4028
- _id: DEP1308
language:
- iso: eng
publication_status: published
status: public
title: 'FoodLifeTimeTracking: Datengetriebene dynamische Haltbarkeitsvorhersage von
Erfrischungsgetränken'
type: conference_speech
user_id: '81304'
year: '2024'
...
---
_id: '12021'
author:
- first_name: Jan
full_name: Segermann, Jan
id: '81965'
last_name: Segermann
- first_name: Mario
full_name: Luttmann, Mario
id: '63215'
last_name: Luttmann
- first_name: André
full_name: Blome, André
id: '62117'
last_name: Blome
- first_name: Sebastian
full_name: Feldt, Sebastian
id: '61469'
last_name: Feldt
- first_name: Sujee
full_name: Sivanesan, Sujee
last_name: Sivanesan
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
- first_name: Björn
full_name: Frahm, Björn
id: '45666'
last_name: Frahm
- first_name: Ulrich
full_name: Müller, Ulrich
id: '12119'
last_name: Müller
citation:
ama: 'Segermann J, Luttmann M, Blome A, et al. Die Rolle von ML-Modellen in der
Lebensmitteltechnologie: Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie.;
2024.'
apa: 'Segermann, J., Luttmann, M., Blome, A., Feldt, S., Sivanesan, S., Holst, C.-A.,
Lohweg, V., Frahm, B., & Müller, U. (2024). Die Rolle von ML-Modellen in
der Lebensmitteltechnologie: Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie.
10. GDL Kongress Lebensmitteltechnologie 2024, Lemgo.'
bjps: 'Segermann J et al. (2024) Die Rolle von ML-Modellen in der
Lebensmitteltechnologie: Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie.
.'
chicago: 'Segermann, Jan, Mario Luttmann, André Blome, Sebastian Feldt, Sujee Sivanesan,
Christoph-Alexander Holst, Volker Lohweg, Björn Frahm, and Ulrich Müller. Die
Rolle von ML-Modellen in der Lebensmitteltechnologie: Eine Fallstudie zur Sauerteigfermentation
mit NIR-Spektroskopie, 2024.'
chicago-de: 'Segermann, Jan, Mario Luttmann, André Blome, Sebastian Feldt, Sujee
Sivanesan, Christoph-Alexander Holst, Volker Lohweg, Björn Frahm und Ulrich Müller.
2024. Die Rolle von ML-Modellen in der Lebensmitteltechnologie: Eine Fallstudie
zur Sauerteigfermentation mit NIR-Spektroskopie.'
din1505-2-1: 'Segermann,
Jan ; Luttmann, Mario ; Blome, André ; Feldt,
Sebastian ; Sivanesan, Sujee
; Holst, Christoph-Alexander ; Lohweg, Volker ; Frahm,
Björn ; u. a.: Die Rolle von ML-Modellen in der Lebensmitteltechnologie:
Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie, 2024'
havard: 'J. Segermann, M. Luttmann, A. Blome, S. Feldt, S. Sivanesan, C.-A. Holst,
V. Lohweg, B. Frahm, U. Müller, Die Rolle von ML-Modellen in der Lebensmitteltechnologie:
Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie, 2024.'
ieee: 'J. Segermann et al., Die Rolle von ML-Modellen in der Lebensmitteltechnologie:
Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie. 2024.'
mla: 'Segermann, Jan, et al. Die Rolle von ML-Modellen in der Lebensmitteltechnologie:
Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie. 2024.'
short: 'J. Segermann, M. Luttmann, A. Blome, S. Feldt, S. Sivanesan, C.-A. Holst,
V. Lohweg, B. Frahm, U. Müller, Die Rolle von ML-Modellen in der Lebensmitteltechnologie:
Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie, 2024.'
ufg: 'Segermann, Jan u. a.: Die Rolle von ML-Modellen in der Lebensmitteltechnologie:
Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie, o. O. 2024.'
van: 'Segermann J, Luttmann M, Blome A, Feldt S, Sivanesan S, Holst CA, et al. Die
Rolle von ML-Modellen in der Lebensmitteltechnologie: Eine Fallstudie zur Sauerteigfermentation
mit NIR-Spektroskopie. 2024.'
conference:
end_date: 2024-10-12
location: Lemgo
name: 10. GDL Kongress Lebensmitteltechnologie 2024
start_date: 2024-10-10
date_created: 2024-11-06T16:53:13Z
date_updated: 2025-10-17T18:22:39Z
department:
- _id: DEP4028
- _id: DEP5023
- _id: DEP4000
- _id: DEP1308
keyword:
- sourdough
- fermentation
- near-infrared spectroscopy
- support vector machine
language:
- iso: ger
publication_status: published
status: public
title: 'Die Rolle von ML-Modellen in der Lebensmitteltechnologie: Eine Fallstudie
zur Sauerteigfermentation mit NIR-Spektroskopie'
type: conference_speech
user_id: '81304'
year: '2024'
...
---
_id: '1993'
abstract:
- lang: eng
text: Industrial applications put special demands on machine learning algorithms.
Noisy data, outliers, and sensor faults present an immense challenge for learners.
A considerable part of machine learning research focuses on the selection of relevant,
non-redundant features. This contribution details an approach to group and fuse
redundant features prior to learning and classification. Features are grouped
relying on a correlation-based redundancy measure. The fusion of features is guided
by determining the majority observation based on possibility distributions. Furthermore,
this paper studies the effects of feature fusion on the robustness and performance
of classification with a focus on industrial applications. The approach is statistically
evaluated on public datasets in comparison to classification on selected features
only.
author:
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Holst C-A, Lohweg V. Feature Fusion to Increase the Robustness of Machine
Learners in Industrial Environments. In: At - Automatisierungstechnik 67 (10)
. De Gruyter; 2019:853-865.'
apa: Holst, C.-A., & Lohweg, V. (2019). Feature Fusion to Increase the Robustness
of Machine Learners in Industrial Environments. In at - Automatisierungstechnik
67 (10) (pp. 853–865). De Gruyter.
bjps: Holst C-A and Lohweg V (2019) Feature Fusion to Increase the Robustness
of Machine Learners in Industrial Environments. At - Automatisierungstechnik
67 (10) . De Gruyter, pp. 853–865.
chicago: Holst, Christoph-Alexander, and Volker Lohweg. “Feature Fusion to Increase
the Robustness of Machine Learners in Industrial Environments.” In At - Automatisierungstechnik
67 (10) , 853–65. De Gruyter, 2019.
chicago-de: 'Holst, Christoph-Alexander und Volker Lohweg. 2019. Feature Fusion
to Increase the Robustness of Machine Learners in Industrial Environments. In:
at - Automatisierungstechnik 67 (10) , 853–865. De Gruyter.'
din1505-2-1: 'Holst, Christoph-Alexander
; Lohweg, Volker: Feature Fusion
to Increase the Robustness of Machine Learners in Industrial Environments. In:
at - Automatisierungstechnik 67 (10) : De Gruyter, 2019, S. 853–865'
havard: 'C.-A. Holst, V. Lohweg, Feature Fusion to Increase the Robustness of Machine
Learners in Industrial Environments, in: At - Automatisierungstechnik 67 (10)
, De Gruyter, 2019: pp. 853–865.'
ieee: C.-A. Holst and V. Lohweg, “Feature Fusion to Increase the Robustness of Machine
Learners in Industrial Environments,” in at - Automatisierungstechnik 67 (10)
, 2019, pp. 853–865.
mla: Holst, Christoph-Alexander, and Volker Lohweg. “Feature Fusion to Increase
the Robustness of Machine Learners in Industrial Environments.” At - Automatisierungstechnik
67 (10) , De Gruyter, 2019, pp. 853–65.
short: 'C.-A. Holst, V. Lohweg, in: At - Automatisierungstechnik 67 (10) , De Gruyter,
2019, pp. 853–865.'
ufg: 'Holst, Christoph-Alexander/Lohweg, Volker (2019): Feature Fusion to
Increase the Robustness of Machine Learners in Industrial Environments, in: at
- Automatisierungstechnik 67 (10) , S. 853–865.'
van: 'Holst C-A, Lohweg V. Feature Fusion to Increase the Robustness of Machine
Learners in Industrial Environments. In: at - Automatisierungstechnik 67 (10)
. De Gruyter; 2019. p. 853–65.'
date_created: 2019-11-22T12:51:13Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
language:
- iso: eng
page: 853-865
publication: 'at - Automatisierungstechnik 67 (10) '
publisher: De Gruyter
status: public
title: Feature Fusion to Increase the Robustness of Machine Learners in Industrial
Environments
type: conference
user_id: '74004'
year: 2019
...
---
_id: '1995'
abstract:
- lang: eng
text: The repair of carbon fibre reinforced polymer structures of aircraft is increasingly
conducted on site. Monitoring the curing process of polymers has the potential
to decrease repair costs by time optimisation and quality control. In this paper
Lamb waves are utilised to determine the degree of cure. Waves are excited and
recorded by two piezoelectric transducers, one serving as an actuator and the
other as a sensor. The recorded signals are processed with a complex wavelet transform,
which allows more accurate feature extraction than calculating features in time
domain. Extracted features are the transmitted signal energy of the wave and the
resonance frequency of the curing polymer. Waves are excited at different frequencies
to identify the current resonance frequency. Excitation at or near the current
resonant frequency ensures that curing is monitored with maximum sensitivity.
author:
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Kristian
full_name: Röckemann, Kristian
last_name: Röckemann
- first_name: Andreas
full_name: Steinmetz, Andreas
id: '55232'
last_name: Steinmetz
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Holst C-A, Röckemann K, Steinmetz A, Lohweg V. Lamb wave-based Cure Monitoring
of Carbon Fibre Reinforced Polymers for On-site Aircraft Repairs. In: 5th IEEE
International Forum on Research and Technologies for Society and Industry.
Firenze, Italy; 2019.'
apa: Holst, C.-A., Röckemann, K., Steinmetz, A., & Lohweg, V. (2019). Lamb wave-based
Cure Monitoring of Carbon Fibre Reinforced Polymers for On-site Aircraft Repairs.
In 5th IEEE International Forum on Research and Technologies for Society and
Industry. Firenze, Italy.
bjps: Holst C-A et al. (2019) Lamb Wave-Based Cure Monitoring of Carbon
Fibre Reinforced Polymers for On-Site Aircraft Repairs. 5th IEEE International
Forum on Research and Technologies for Society and Industry. Firenze, Italy.
chicago: Holst, Christoph-Alexander, Kristian Röckemann, Andreas Steinmetz, and
Volker Lohweg. “Lamb Wave-Based Cure Monitoring of Carbon Fibre Reinforced Polymers
for On-Site Aircraft Repairs.” In 5th IEEE International Forum on Research
and Technologies for Society and Industry. Firenze, Italy, 2019.
chicago-de: 'Holst, Christoph-Alexander, Kristian Röckemann, Andreas Steinmetz und
Volker Lohweg. 2019. Lamb wave-based Cure Monitoring of Carbon Fibre Reinforced
Polymers for On-site Aircraft Repairs. In: 5th IEEE International Forum on
Research and Technologies for Society and Industry. Firenze, Italy.'
din1505-2-1: 'Holst, Christoph-Alexander
; Röckemann, Kristian ; Steinmetz,
Andreas ; Lohweg, Volker:
Lamb wave-based Cure Monitoring of Carbon Fibre Reinforced Polymers for On-site
Aircraft Repairs. In: 5th IEEE International Forum on Research and Technologies
for Society and Industry. Firenze, Italy, 2019'
havard: 'C.-A. Holst, K. Röckemann, A. Steinmetz, V. Lohweg, Lamb wave-based Cure
Monitoring of Carbon Fibre Reinforced Polymers for On-site Aircraft Repairs, in:
5th IEEE International Forum on Research and Technologies for Society and Industry,
Firenze, Italy, 2019.'
ieee: C.-A. Holst, K. Röckemann, A. Steinmetz, and V. Lohweg, “Lamb wave-based Cure
Monitoring of Carbon Fibre Reinforced Polymers for On-site Aircraft Repairs,”
in 5th IEEE International Forum on Research and Technologies for Society and
Industry, 2019.
mla: Holst, Christoph-Alexander, et al. “Lamb Wave-Based Cure Monitoring of Carbon
Fibre Reinforced Polymers for On-Site Aircraft Repairs.” 5th IEEE International
Forum on Research and Technologies for Society and Industry, 2019.
short: 'C.-A. Holst, K. Röckemann, A. Steinmetz, V. Lohweg, in: 5th IEEE International
Forum on Research and Technologies for Society and Industry, Firenze, Italy, 2019.'
ufg: 'Holst, Christoph-Alexander et. al. (2019): Lamb wave-based Cure Monitoring
of Carbon Fibre Reinforced Polymers for On-site Aircraft Repairs, in: 5th IEEE
International Forum on Research and Technologies for Society and Industry,
Firenze, Italy.'
van: 'Holst C-A, Röckemann K, Steinmetz A, Lohweg V. Lamb wave-based Cure Monitoring
of Carbon Fibre Reinforced Polymers for On-site Aircraft Repairs. In: 5th IEEE
International Forum on Research and Technologies for Society and Industry. Firenze,
Italy; 2019.'
date_created: 2019-11-22T12:51:16Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
language:
- iso: eng
place: Firenze, Italy
publication: 5th IEEE International Forum on Research and Technologies for Society
and Industry
status: public
title: Lamb wave-based Cure Monitoring of Carbon Fibre Reinforced Polymers for On-site
Aircraft Repairs
type: conference
user_id: '74004'
year: 2019
...
---
_id: '1998'
author:
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Holst C-A, Lohweg V. Improving Majority-guided Fuzzy Information Fusion for
Industry 4.0 Condition Monitoring. In: 22nd International Conference on Information
Fusion (FUSION). Ottawa, Canada; 2019.'
apa: Holst, C.-A., & Lohweg, V. (2019). Improving Majority-guided Fuzzy Information
Fusion for Industry 4.0 Condition Monitoring. In 22nd International Conference
on Information Fusion (FUSION). Ottawa, Canada.
bjps: Holst C-A and Lohweg V (2019) Improving Majority-Guided Fuzzy Information
Fusion for Industry 4.0 Condition Monitoring. 22nd International Conference
on Information Fusion (FUSION). Ottawa, Canada.
chicago: Holst, Christoph-Alexander, and Volker Lohweg. “Improving Majority-Guided
Fuzzy Information Fusion for Industry 4.0 Condition Monitoring.” In 22nd International
Conference on Information Fusion (FUSION). Ottawa, Canada, 2019.
chicago-de: 'Holst, Christoph-Alexander und Volker Lohweg. 2019. Improving Majority-guided
Fuzzy Information Fusion for Industry 4.0 Condition Monitoring. In: 22nd International
Conference on Information Fusion (FUSION). Ottawa, Canada.'
din1505-2-1: 'Holst, Christoph-Alexander
; Lohweg, Volker: Improving Majority-guided
Fuzzy Information Fusion for Industry 4.0 Condition Monitoring. In: 22nd International
Conference on Information Fusion (FUSION). Ottawa, Canada, 2019'
havard: 'C.-A. Holst, V. Lohweg, Improving Majority-guided Fuzzy Information Fusion
for Industry 4.0 Condition Monitoring, in: 22nd International Conference on Information
Fusion (FUSION), Ottawa, Canada, 2019.'
ieee: C.-A. Holst and V. Lohweg, “Improving Majority-guided Fuzzy Information Fusion
for Industry 4.0 Condition Monitoring,” in 22nd International Conference on
Information Fusion (FUSION), 2019.
mla: Holst, Christoph-Alexander, and Volker Lohweg. “Improving Majority-Guided Fuzzy
Information Fusion for Industry 4.0 Condition Monitoring.” 22nd International
Conference on Information Fusion (FUSION), 2019.
short: 'C.-A. Holst, V. Lohweg, in: 22nd International Conference on Information
Fusion (FUSION), Ottawa, Canada, 2019.'
ufg: 'Holst, Christoph-Alexander/Lohweg, Volker (2019): Improving Majority-guided
Fuzzy Information Fusion for Industry 4.0 Condition Monitoring, in: 22nd International
Conference on Information Fusion (FUSION), Ottawa, Canada.'
van: 'Holst C-A, Lohweg V. Improving Majority-guided Fuzzy Information Fusion for
Industry 4.0 Condition Monitoring. In: 22nd International Conference on Information
Fusion (FUSION). Ottawa, Canada; 2019.'
date_created: 2019-11-22T12:51:20Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
language:
- iso: eng
place: Ottawa, Canada
publication: 22nd International Conference on Information Fusion (FUSION)
status: public
title: Improving Majority-guided Fuzzy Information Fusion for Industry 4.0 Condition
Monitoring
type: conference
user_id: '68554'
year: 2019
...
---
_id: '2003'
abstract:
- lang: eng
text: On-site aircraft repairs are gaining in importance due to the susceptibility
of carbon fibre reinforced polymers to damage. Repairs themselves are required
to be inspected for quality, preferably cost- and time-efficiently. This paper
presents an approach for the inspection of repaired composites based on guided
Lamb waves. The focus is on cost-effective signal excitation and effective signal
processing. Lamb waves are excited with piezoelectric transducers at the resonance
frequency of the material under test. Measured signals are processed with a complex
wavelet transform to improve damage detection. The proposed approach is evaluated
on two test specimens, one of which has a defect in the adhesive bond.
author:
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Kristian
full_name: Röckemann, Kristian
last_name: Röckemann
- first_name: Andreas
full_name: Steinmetz, Andreas
id: '55232'
last_name: Steinmetz
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Holst C-A, Röckemann K, Steinmetz A, Lohweg V. Lamb Wave-based Quality Inspection
of Repaired Carbon Fibre Reinforced Polymers for On-Site Aircraft Maintenance.
In: 24nd IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA2019). Zaragoza, Spain; 2019.'
apa: Holst, C.-A., Röckemann, K., Steinmetz, A., & Lohweg, V. (2019). Lamb Wave-based
Quality Inspection of Repaired Carbon Fibre Reinforced Polymers for On-Site Aircraft
Maintenance. In 24nd IEEE International Conference on Emerging Technologies
and Factory Automation (ETFA2019). Zaragoza, Spain.
bjps: Holst C-A et al. (2019) Lamb Wave-Based Quality Inspection of
Repaired Carbon Fibre Reinforced Polymers for On-Site Aircraft Maintenance. 24nd
IEEE International Conference on Emerging Technologies and Factory Automation
(ETFA2019). Zaragoza, Spain.
chicago: Holst, Christoph-Alexander, Kristian Röckemann, Andreas Steinmetz, and
Volker Lohweg. “Lamb Wave-Based Quality Inspection of Repaired Carbon Fibre Reinforced
Polymers for On-Site Aircraft Maintenance.” In 24nd IEEE International Conference
on Emerging Technologies and Factory Automation (ETFA2019). Zaragoza, Spain,
2019.
chicago-de: 'Holst, Christoph-Alexander, Kristian Röckemann, Andreas Steinmetz und
Volker Lohweg. 2019. Lamb Wave-based Quality Inspection of Repaired Carbon Fibre
Reinforced Polymers for On-Site Aircraft Maintenance. In: 24nd IEEE International
Conference on Emerging Technologies and Factory Automation (ETFA2019). Zaragoza,
Spain.'
din1505-2-1: 'Holst, Christoph-Alexander
; Röckemann, Kristian ; Steinmetz,
Andreas ; Lohweg, Volker:
Lamb Wave-based Quality Inspection of Repaired Carbon Fibre Reinforced Polymers
for On-Site Aircraft Maintenance. In: 24nd IEEE International Conference on
Emerging Technologies and Factory Automation (ETFA2019). Zaragoza, Spain,
2019'
havard: 'C.-A. Holst, K. Röckemann, A. Steinmetz, V. Lohweg, Lamb Wave-based Quality
Inspection of Repaired Carbon Fibre Reinforced Polymers for On-Site Aircraft Maintenance,
in: 24nd IEEE International Conference on Emerging Technologies and Factory Automation
(ETFA2019), Zaragoza, Spain, 2019.'
ieee: C.-A. Holst, K. Röckemann, A. Steinmetz, and V. Lohweg, “Lamb Wave-based Quality
Inspection of Repaired Carbon Fibre Reinforced Polymers for On-Site Aircraft Maintenance,”
in 24nd IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA2019), 2019.
mla: Holst, Christoph-Alexander, et al. “Lamb Wave-Based Quality Inspection of Repaired
Carbon Fibre Reinforced Polymers for On-Site Aircraft Maintenance.” 24nd IEEE
International Conference on Emerging Technologies and Factory Automation (ETFA2019),
2019.
short: 'C.-A. Holst, K. Röckemann, A. Steinmetz, V. Lohweg, in: 24nd IEEE International
Conference on Emerging Technologies and Factory Automation (ETFA2019), Zaragoza,
Spain, 2019.'
ufg: 'Holst, Christoph-Alexander et. al. (2019): Lamb Wave-based Quality
Inspection of Repaired Carbon Fibre Reinforced Polymers for On-Site Aircraft Maintenance,
in: 24nd IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA2019), Zaragoza, Spain.'
van: 'Holst C-A, Röckemann K, Steinmetz A, Lohweg V. Lamb Wave-based Quality Inspection
of Repaired Carbon Fibre Reinforced Polymers for On-Site Aircraft Maintenance.
In: 24nd IEEE International Conference on Emerging Technologies and Factory Automation
(ETFA2019). Zaragoza, Spain; 2019.'
date_created: 2019-11-22T12:54:24Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
language:
- iso: eng
place: Zaragoza, Spain
publication: 24nd IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA2019)
status: public
title: Lamb Wave-based Quality Inspection of Repaired Carbon Fibre Reinforced Polymers
for On-Site Aircraft Maintenance
type: conference
user_id: '74004'
year: 2019
...
---
_id: '2007'
abstract:
- lang: eng
text: Multisensor systems are susceptible to sensor ageing effects as well as to
environmental changes. Due to these effects, the distribution of sensor measurements
may change over time, which is referred to as sensor drift. A multisensor system
which adapts to drift by self-monitoring is more durable, requires less manual
maintenance, and provides information of higher quality. This contribution proposes
an approach for detecting and adapting to sensor drift. The proposed detection
algorithm determines the reliability of a sensor based on fuzzy pattern classifiers
and a consistency measure. By this means, the inherent redundancy in multisensor
systems is exploited to detect drift. Detected drift leads then to a retraining
of the classifier on batched data guided by information fusion. The retraining
incorporates the estimated magnitude of the drift. The proposed algorithms are
evaluated in comparison with state-of-the-art methods in the scope of a publicly
available dataset. It is shown that the drift detection algorithm yields results
similar to the benchmark algorithm but is less computationally complex. Relearning
with the drift-adapted approach results in more robust classifiers with regard
to potential future drift.
author:
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Holst C-A, Lohweg V. A Conflict-Based Drift Detection And Adaptation Approach
for Multisensor Information Fusion. In: 23rd IEEE International Conference
on Emerging Technologies and Factory Automation (ETFA). Torino, Italy; 2018.
doi:10.1109/ETFA.2018.8502571'
apa: Holst, C.-A., & Lohweg, V. (2018). A Conflict-Based Drift Detection And
Adaptation Approach for Multisensor Information Fusion. In 23rd IEEE International
Conference on Emerging Technologies and Factory Automation (ETFA). Torino,
Italy. https://doi.org/10.1109/ETFA.2018.8502571
bjps: Holst C-A and Lohweg V (2018) A Conflict-Based Drift Detection And
Adaptation Approach for Multisensor Information Fusion. 23rd IEEE International
Conference on Emerging Technologies and Factory Automation (ETFA). Torino,
Italy.
chicago: Holst, Christoph-Alexander, and Volker Lohweg. “A Conflict-Based Drift
Detection And Adaptation Approach for Multisensor Information Fusion.” In 23rd
IEEE International Conference on Emerging Technologies and Factory Automation
(ETFA). Torino, Italy, 2018. https://doi.org/10.1109/ETFA.2018.8502571.
chicago-de: 'Holst, Christoph-Alexander und Volker Lohweg. 2018. A Conflict-Based
Drift Detection And Adaptation Approach for Multisensor Information Fusion. In:
23rd IEEE International Conference on Emerging Technologies and Factory Automation
(ETFA). Torino, Italy. doi:10.1109/ETFA.2018.8502571,
.'
din1505-2-1: 'Holst, Christoph-Alexander
; Lohweg, Volker: A Conflict-Based
Drift Detection And Adaptation Approach for Multisensor Information Fusion. In:
23rd IEEE International Conference on Emerging Technologies and Factory Automation
(ETFA). Torino, Italy, 2018'
havard: 'C.-A. Holst, V. Lohweg, A Conflict-Based Drift Detection And Adaptation
Approach for Multisensor Information Fusion, in: 23rd IEEE International Conference
on Emerging Technologies and Factory Automation (ETFA), Torino, Italy, 2018.'
ieee: C.-A. Holst and V. Lohweg, “A Conflict-Based Drift Detection And Adaptation
Approach for Multisensor Information Fusion,” in 23rd IEEE International Conference
on Emerging Technologies and Factory Automation (ETFA), Torino, Italy, 2018.
mla: Holst, Christoph-Alexander, and Volker Lohweg. “A Conflict-Based Drift Detection
And Adaptation Approach for Multisensor Information Fusion.” 23rd IEEE International
Conference on Emerging Technologies and Factory Automation (ETFA), 2018, doi:10.1109/ETFA.2018.8502571.
short: 'C.-A. Holst, V. Lohweg, in: 23rd IEEE International Conference on Emerging
Technologies and Factory Automation (ETFA), Torino, Italy, 2018.'
ufg: 'Holst, Christoph-Alexander/Lohweg, Volker (2018): A Conflict-Based
Drift Detection And Adaptation Approach for Multisensor Information Fusion, in:
23rd IEEE International Conference on Emerging Technologies and Factory Automation
(ETFA), Torino, Italy.'
van: 'Holst C-A, Lohweg V. A Conflict-Based Drift Detection And Adaptation Approach
for Multisensor Information Fusion. In: 23rd IEEE International Conference on
Emerging Technologies and Factory Automation (ETFA). Torino, Italy; 2018.'
conference:
end_date: 2018-09-07
location: Torino, Italy
name: IEEE 23rd International Conference on Emerging Technologies and Factory Automation
(ETFA) 2018
start_date: 2018-09-04
date_created: 2019-11-25T08:35:47Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
doi: 10.1109/ETFA.2018.8502571
keyword:
- Multisensor systems
- Temperature measurement
- Current measurement
- Redundancy
- Pollution measurement
- Detection algorithms
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/abstract/document/8502571
place: Torino, Italy
publication: 23rd IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA)
publication_status: published
status: public
title: A Conflict-Based Drift Detection And Adaptation Approach for Multisensor Information
Fusion
type: conference
user_id: '15514'
year: 2018
...
---
_id: '2009'
abstract:
- lang: eng
text: The aim of sensor orchestration is to design and organise multi-sensor systems
both to reduce manual design efforts and to facilitate complex sensor systems.
A sensor orchestration is required to adapt to non-stationary environments, even
if it is applied in streaming data scenarios where labelled data are scarce or
not available. Without labels in dynamic environments, it is challenging to determine
not only the accuracy of a classifier but also its reliability. This contribution
proposes monitoring algorithms intended to support sensor orchestration in classification
tasks in non-stationary environments. Proposed measures regard the relevance of
features, the separability of classes, and the classifier's reliability. The proposed
monitoring algorithms are evaluated regarding their applicability in the scope
of a publicly available and synthetically created collection of datasets. It is
shown that the approach (i) is able to distinguish relevant from irrelevant features,
(ii) measures class separability as class representations drift through feature
space, and (iii) marks a classifier as unreliable if errors in the drift-adaptation
occur.
author:
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Holst C-A, Lohweg V. Supporting Sensor Orchestration in Non-Stationary Environments.
In: ACM International Conference on Computing Frontiers 2018. ACM: New
York, NY ; 2018:363-370. doi:10.1145/3203217.3203228'
apa: 'Holst, C.-A., & Lohweg, V. (2018). Supporting Sensor Orchestration in
Non-Stationary Environments. In ACM International Conference on Computing Frontiers
2018 (pp. 363–370). ACM: New York, NY . https://doi.org/10.1145/3203217.3203228'
bjps: 'Holst C-A and Lohweg V (2018) Supporting Sensor Orchestration in Non-Stationary
Environments. ACM International Conference on Computing Frontiers 2018.
ACM: New York, NY , pp. 363–370.'
chicago: 'Holst, Christoph-Alexander, and Volker Lohweg. “Supporting Sensor Orchestration
in Non-Stationary Environments.” In ACM International Conference on Computing
Frontiers 2018, 363–70. ACM: New York, NY , 2018. https://doi.org/10.1145/3203217.3203228.'
chicago-de: 'Holst, Christoph-Alexander und Volker Lohweg. 2018. Supporting Sensor
Orchestration in Non-Stationary Environments. In: ACM International Conference
on Computing Frontiers 2018, 363–370. ACM: New York, NY . doi:10.1145/3203217.3203228,
.'
din1505-2-1: 'Holst, Christoph-Alexander
; Lohweg, Volker: Supporting Sensor
Orchestration in Non-Stationary Environments. In: ACM International Conference
on Computing Frontiers 2018. ACM : New York, NY , 2018, S. 363–370'
havard: 'C.-A. Holst, V. Lohweg, Supporting Sensor Orchestration in Non-Stationary
Environments, in: ACM International Conference on Computing Frontiers 2018, New
York, NY , ACM, 2018: pp. 363–370.'
ieee: C.-A. Holst and V. Lohweg, “Supporting Sensor Orchestration in Non-Stationary
Environments,” in ACM International Conference on Computing Frontiers 2018,
Ischia, Italy, 2018, pp. 363–370.
mla: Holst, Christoph-Alexander, and Volker Lohweg. “Supporting Sensor Orchestration
in Non-Stationary Environments.” ACM International Conference on Computing
Frontiers 2018, New York, NY , 2018, pp. 363–70, doi:10.1145/3203217.3203228.
short: 'C.-A. Holst, V. Lohweg, in: ACM International Conference on Computing Frontiers
2018, New York, NY , ACM, 2018, pp. 363–370.'
ufg: 'Holst, Christoph-Alexander/Lohweg, Volker (2018): Supporting Sensor
Orchestration in Non-Stationary Environments, in: ACM International Conference
on Computing Frontiers 2018, ACM, S. 363–370.'
van: 'Holst C-A, Lohweg V. Supporting Sensor Orchestration in Non-Stationary Environments.
In: ACM International Conference on Computing Frontiers 2018. ACM: New York,
NY ; 2018. p. 363–70.'
conference:
end_date: 2018-05-10
location: Ischia, Italy
name: '18 Proceedings of the 15th ACM International Conference on Computing '
start_date: 2018-05-08
date_created: 2019-11-25T08:35:50Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
doi: 10.1145/3203217.3203228
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.acm.org/ft_gateway.cfm?id=3203228&ftid=1990918&dwn=1&CFID=118496599&CFTOKEN=78ae977fe9bab251-FBE29E78-FC08-9C3A-B5261CFF94BFEF7E
oa: '1'
page: 363 - 370
place: ACM
publication: ACM International Conference on Computing Frontiers 2018
publication_identifier:
eisbn:
- 978-1-4503-5761-6
publisher: ' New York, NY '
status: public
title: Supporting Sensor Orchestration in Non-Stationary Environments
type: conference
user_id: '15514'
year: 2018
...
---
_id: '2014'
abstract:
- lang: eng
text: Industrial applications are in transition towards modular and flexible architectures
that are capable of self-configuration and -optimisation. This is due to the demand
of mass customisation and the increasing complexity of industrial systems. The
conversion to modular systems is related to challenges in all disciplines. Consequently,
diverse tasks such as information processing, extensive networking, or system
monitoring using sensor and information fusion systems need to be reconsidered.
The focus of this contribution is on distributed sensor and information fusion
systems for system monitoring, which must reflect the increasing flexibility of
fusion systems. This contribution thus proposes an approach, which relies on a
network of self-descriptive intelligent sensor nodes, for the automatic design
and update of sensor and information fusion systems. This article encompasses
the fusion system configuration and adaptation as well as communication aspects.
Manual interaction with the flexibly changing system is reduced to a minimum.
article_number: '601'
author:
- first_name: Alexander
full_name: Fritze, Alexander
last_name: Fritze
- first_name: Uwe
full_name: Mönks, Uwe
id: '1825'
last_name: Mönks
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: Fritze A, Mönks U, Holst C-A, Lohweg V. An Approach to Automated Fusion System
Design and Adaptation. Sensors. 2017;17(3). doi: https://doi.org/10.3390/s17030601
apa: Fritze, A., Mönks, U., Holst, C.-A., & Lohweg, V. (2017). An Approach to
Automated Fusion System Design and Adaptation. Sensors, 17(3). https://doi.org/ https://doi.org/10.3390/s17030601
bjps: Fritze A et al. (2017) An Approach to Automated Fusion System
Design and Adaptation. Sensors 17.
chicago: Fritze, Alexander, Uwe Mönks, Christoph-Alexander Holst, and Volker Lohweg.
“An Approach to Automated Fusion System Design and Adaptation.” Sensors
17, no. 3 (2017). https://doi.org/
https://doi.org/10.3390/s17030601.
chicago-de: Fritze, Alexander, Uwe Mönks, Christoph-Alexander Holst und Volker Lohweg.
2017. An Approach to Automated Fusion System Design and Adaptation. Sensors
17, Nr. 3. doi:
https://doi.org/10.3390/s17030601, .
din1505-2-1: 'Fritze, Alexander ;
Mönks, Uwe ; Holst,
Christoph-Alexander ; Lohweg, Volker:
An Approach to Automated Fusion System Design and Adaptation. In: Sensors
Bd. 17 (2017), Nr. 3'
havard: A. Fritze, U. Mönks, C.-A. Holst, V. Lohweg, An Approach to Automated Fusion
System Design and Adaptation, Sensors. 17 (2017).
ieee: A. Fritze, U. Mönks, C.-A. Holst, and V. Lohweg, “An Approach to Automated
Fusion System Design and Adaptation,” Sensors, vol. 17, no. 3, 2017.
mla: Fritze, Alexander, et al. “An Approach to Automated Fusion System Design and
Adaptation.” Sensors, vol. 17, no. 3, 601, 2017, doi: https://doi.org/10.3390/s17030601.
short: A. Fritze, U. Mönks, C.-A. Holst, V. Lohweg, Sensors 17 (2017).
ufg: 'Fritze, Alexander et. al. (2017): An Approach to Automated Fusion System
Design and Adaptation, in: Sensors 17 (3).'
van: Fritze A, Mönks U, Holst C-A, Lohweg V. An Approach to Automated Fusion System
Design and Adaptation. Sensors. 2017;17(3).
date_created: 2019-11-25T08:52:14Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
doi: ' https://doi.org/10.3390/s17030601'
intvolume: ' 17'
issue: '3'
keyword:
- information fusion
- intelligent sensor
- knowledge-based system
- self-configuration
- sensor fusion
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/1424-8220/17/3/601/htm
oa: '1'
publication: Sensors
publication_identifier:
issn:
- 1424-8220
publication_status: published
status: public
title: An Approach to Automated Fusion System Design and Adaptation
type: journal_article
user_id: '15514'
volume: 17
year: 2017
...
---
_id: '2018'
abstract:
- lang: eng
text: Applying information fusion systems aims at gaining information of higher
quality and simultaneously decreasing computational and communicational efforts.
An increased availability of sensors in industrial machines, but also in everyday
life, results in large amounts of potential features. Each feature entails computational
and communicational costs. An information fusion system may not require all features,
supported by the available sensors, to fulfil its purpose. Feature selection methods
reduce the amount of features with the aim to maintain or even increase performance.
This contribution proposes a feature selection approach exploiting the inherent
conflict between features and utilising a state-ofthe-art information fusion operator.
The performance of the proposed method is evaluated in the scope of a publicly
available data set and benchmarked against an established feature selection method.
It is shown that the proposed approach is faster and produces more accurate feature
subsets containing very few features, although the established method produces
slightly better performing subsets for large feature subsets.
author:
- first_name: Christoph-Alexander
full_name: Holst, Christoph-Alexander
id: '64782'
last_name: Holst
- first_name: Uwe
full_name: Mönks, Uwe
id: '1825'
last_name: Mönks
- first_name: Volker
full_name: Lohweg, Volker
id: '1804'
last_name: Lohweg
orcid: 0000-0002-3325-7887
citation:
ama: 'Holst C-A, Mönks U, Lohweg V. Conflict-based Feature Selection for Information
Fusion Systems. In: Dortmund: 27. Workshop Computational Intelligence VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA); 2017:279-295. doi:10.5445/KSP/1000074341'
apa: 'Holst, C.-A., Mönks, U., & Lohweg, V. (2017). Conflict-based Feature Selection
for Information Fusion Systems (pp. 279–295). Presented at the 27. Workshop Computational
Intelligence , Dortmund: 27. Workshop Computational Intelligence VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA). https://doi.org/10.5445/KSP/1000074341'
bjps: 'Holst C-A, Mönks U and Lohweg V (2017) Conflict-Based Feature Selection
for Information Fusion Systems. Dortmund: 27. Workshop Computational Intelligence
VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA), pp. 279–295.'
chicago: 'Holst, Christoph-Alexander, Uwe Mönks, and Volker Lohweg. “Conflict-Based
Feature Selection for Information Fusion Systems,” 279–95. Dortmund: 27. Workshop
Computational Intelligence VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik
(GMA), 2017. https://doi.org/10.5445/KSP/1000074341.'
chicago-de: 'Holst, Christoph-Alexander, Uwe Mönks und Volker Lohweg. 2017. Conflict-based
Feature Selection for Information Fusion Systems. In: , 279–295. Dortmund: 27.
Workshop Computational Intelligence VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik
(GMA). doi:10.5445/KSP/1000074341,
.'
din1505-2-1: 'Holst, Christoph-Alexander
; Mönks, Uwe ; Lohweg,
Volker: Conflict-based Feature Selection for Information Fusion Systems.
In: . Dortmund : 27. Workshop Computational Intelligence VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA), 2017, S. 279–295'
havard: 'C.-A. Holst, U. Mönks, V. Lohweg, Conflict-based Feature Selection for
Information Fusion Systems, in: 27. Workshop Computational Intelligence VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA), Dortmund, 2017: pp. 279–295.'
ieee: C.-A. Holst, U. Mönks, and V. Lohweg, “Conflict-based Feature Selection for
Information Fusion Systems,” presented at the 27. Workshop Computational Intelligence
, Dortmund, 2017, pp. 279–295.
mla: Holst, Christoph-Alexander, et al. Conflict-Based Feature Selection for
Information Fusion Systems. 27. Workshop Computational Intelligence VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA), 2017, pp. 279–95, doi:10.5445/KSP/1000074341.
short: 'C.-A. Holst, U. Mönks, V. Lohweg, in: 27. Workshop Computational Intelligence
VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA), Dortmund, 2017,
pp. 279–295.'
ufg: 'Holst, Christoph-Alexander et. al. (2017): Conflict-based Feature Selection
for Information Fusion Systems, in: , Dortmund, S. 279–295.'
van: 'Holst C-A, Mönks U, Lohweg V. Conflict-based Feature Selection for Information
Fusion Systems. In Dortmund: 27. Workshop Computational Intelligence VDI/VDE-Gesellschaft
Mess- und Automatisierungstechnik (GMA); 2017. p. 279–95.'
conference:
end_date: 2017-11-24
location: Dortmund
name: '27. Workshop Computational Intelligence '
start_date: 2017-11-23
date_created: 2019-11-25T09:06:44Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
doi: 10.5445/KSP/1000074341
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://d-nb.info/1147444048/34#page=291
oa: '1'
page: 279-295
place: Dortmund
publication_identifier:
eisbn:
- 978-3-7315-0726-0
publication_status: published
publisher: 27. Workshop Computational Intelligence VDI/VDE-Gesellschaft Mess- und
Automatisierungstechnik (GMA)
status: public
title: Conflict-based Feature Selection for Information Fusion Systems
type: conference
user_id: '15514'
year: 2017
...