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Sandra Rothe
Sandra Rothe
Wissenschaftliche Mitarbeiterin
Bestätigte E-Mail-Adresse bei uni-due.de
Titel
Zitiert von
Zitiert von
Jahr
Does classifier fusion improve the overall performance? Numerical analysis of data and fusion method characteristics influencing classifier fusion performance
S Rothe, B Kudszus, D Söffker
Entropy 21 (9), 866, 2019
182019
Comparison of different information fusion methods using ensemble selection considering benchmark data
S Rothe, D Söffker
2016 19th International Conference on Information Fusion (FUSION), 73-78, 2016
122016
A novel feature-based probability of detection assessment and fusion approach for reliability evaluation of vibration-based diagnosis systems
DA Ameyaw, S Rothe, D Söffker
Structural Health Monitoring 19 (3), 649-660, 2020
92020
New Approaches for Supervision of Systems with Sliding Wear: Fundamental Problems and Experimental Results Using Different Approaches
D Söffker, S Rothe
Applied Sciences 7 (8), 843, 2017
92017
Application of diagnosis and prognosis to wind turbine system based on fatigue load
N Beganovic, JG Njiri, S Rothe, D Söffker
2015 ieee conference on prognostics and health management (phm), 1-6, 2015
92015
Smart, Tough and Successful: Three New Innovative Approaches for Diagnosis and Prognosis of Technical Systems
D SÖFFKER, S Rothe, S Schiffer, H Aljoumaa, D Baccar
Structural Health Monitoring 2013, 2013
92013
Lane changing behavior recognition based on artificial neural network-based state machine approach
R David, S Rothe, D Soffker
2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021
62021
Probability of detection (POD)-oriented view to fault diagnosis for reliability assessment of FDI approaches
DA Ameyaw, S Rothe, D Söffker
International Design Engineering Technical Conferences and Computers and …, 2018
52018
Adaptation and implementation of Probability of Detection (POD)-based fault diagnosis in elastic structures through vibration-based SHM approach
DA Ameyaw, S Rothe, D Söffker
9th European Workshop on Structural Health Monitoring, 2018
52018
State machine approach for lane changing driving behavior recognition
R David, S Rothe, D Söffker
Automation 1 (1), 68-79, 2020
42020
About the reliability of diagnostic statements: fundamentals about detection rates, false alarms, and technical requirements
S Rothe
Deutsche Nationalbibliothek, 2016
42016
Establishing a wear-related deterioration model based on experimental data
N Beganovic, S Rothe, D Söffker
EWSHM-7th European Workshop on Structural Health Monitoring, 2014
42014
Fault diagnosis using Probability of Detection (POD)‐based sensor/information fusion for vibration‐based analysis of elastic structures
DA Ameyaw, S Rothe, D Söffker
PAMM 18 (1), e201800474, 2018
32018
Development of a state-related evaluation for diagnostic-oriented data filtering approach
S Rothe, D SÖFFKER
Structural Health Monitoring 2015, 2015
32015
Ensuring the Reliability of Damage Detection in Composites by Fusion of Differently Classified Acoustic Emission Measurements
S ROTHE, SF WIRTZ, G KAMPMANN, O NELLES, D SÖFFKER
Structural Health Monitoring 2017, 2017
22017
Identification of diagnostic and prognostic features by means of AE and hydraulic pressure measurements
N Beganovic, S Rothe, D Söffker
Proceedings of 8th European Workshop on Structural Health Monitoring, Bilbao …, 2016
22016
Wear-oriented state-of-health calculation and classification using operating data
S Rothe, D Söffker
EWSHM-7th European Workshop on Structural Health Monitoring, 2014
22014
Classifiation of Systems' Health Condition Using the New Adaptive Fuzzy-Based Feature Classification Approach AFFCA in Comparison to a Macro-Data-Based Approach
S Schiffer, S Rothe, D Baccar, D Söffker
EWSHM-7th European Workshop on Structural Health Monitoring, 2014
22014
Does the precision value influence the fusion performance? A method-based experimental study
S Rothe, D Söffker
European Workshop on Structural Health Monitoring, 754-764, 2020
12020
Reliable information fusion methods for condition monitoring
S Rothe
Dissertation, Duisburg, Essen, Universität Duisburg-Essen, 2019, 2019
12019
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