@misc{HentschelTschoepeHoffmannetal., author = {Hentschel, Dieter and Tsch{\"o}pe, Constanze and Hoffmann, R{\"u}diger and Eichner, Matthias and Wolff, Matthias}, title = {Device and method for assessing a quality class of an object to be tested}, language = {de} } @inproceedings{TschoepeWolffHoffmann, author = {Tsch{\"o}pe, Constanze and Wolff, Matthias and Hoffmann, R{\"u}diger}, title = {Automatische Klassifikationsverfahren in der Zustands {\"U}berwachung}, series = {ZfP in Forschung, Entwicklung und Anwendung, M{\"u}nster, 18.-20. Mai 2009, DGZfP-Jahrestagung 2009 Zerst{\"o}rungsfreie Materialpr{\"u}fung}, booktitle = {ZfP in Forschung, Entwicklung und Anwendung, M{\"u}nster, 18.-20. Mai 2009, DGZfP-Jahrestagung 2009 Zerst{\"o}rungsfreie Materialpr{\"u}fung}, publisher = {DGZfP}, address = {Berlin}, isbn = {978-3-940283-16-0}, pages = {5}, language = {de} } @inproceedings{TschoepeWolffStrechaetal., author = {Tsch{\"o}pe, Constanze and Wolff, Matthias and Strecha, Guntram and Duckhorn, Frank and Feher, Thomas and Hoffmann, R{\"u}diger}, title = {Automatisierte Weichheitspr{\"u}fung von Papier}, series = {ZfP in Forschung, Entwicklung und Anwendung, Graz, 17. - 19. September 2012, DACH-Jahrestagung 2012 Zerst{\"o}rungsfreie Materialpr{\"u}fung}, booktitle = {ZfP in Forschung, Entwicklung und Anwendung, Graz, 17. - 19. September 2012, DACH-Jahrestagung 2012 Zerst{\"o}rungsfreie Materialpr{\"u}fung}, publisher = {DGZfP}, address = {Berlin}, isbn = {978-394-02834-4-3}, language = {de} } @techreport{DuckhornWolffTschoepe, author = {Duckhorn, Frank and Wolff, Matthias and Tsch{\"o}pe, Constanze}, title = {Hidden Markov Model training using Finite State Machines}, publisher = {Technische Universit{\"a}t, Institut f{\"u}r Akustik und Sprachkommunikation}, address = {Dresden}, language = {de} } @misc{TschoepeWolffBorchers, author = {Tsch{\"o}pe, Constanze and Wolff, Matthias and Borchers, B.}, title = {Verfahren zur Bestimmung der Weichheit von Tissuepapier}, language = {de} } @misc{HentschelTschoepeHoffmannetal., author = {Hentschel, Dieter and Tsch{\"o}pe, Constanze and Hoffmann, R{\"u}diger and Eichner, Matthias and Wolff, Matthias}, title = {Vorrichtung und Verfahren zur Beurteilung einer G{\"u}teklasse eines zu pr{\"u}fenden Objekts}, language = {de} } @inproceedings{TschoepeJoneitDuckhornetal., author = {Tsch{\"o}pe, Constanze and Joneit, Dieter and Duckhorn, Frank and Strecha, Guntram and Hoffmann, R{\"u}diger and Wolff, Matthias}, title = {Voice control for measurement devices}, series = {AIA-DAGA 2013, proceedings of the International Conference on Acoustics , 18 - 21 March 2013 in Merano}, booktitle = {AIA-DAGA 2013, proceedings of the International Conference on Acoustics , 18 - 21 March 2013 in Merano}, publisher = {DEGA}, address = {Berlin}, language = {en} } @inproceedings{TschoepeWolff, author = {Tsch{\"o}pe, Constanze and Wolff, Matthias}, title = {Zahnradpr{\"u}fung mit statistischen Klassifikatoren}, series = {ZfP in Forschung, Entwicklung und Anwendung, Dresden, 6. - 8. Mai 2013, DGZfP-Jahrestagung 2013 Zerst{\"o}rungsfreie Materialpr{\"u}fung}, booktitle = {ZfP in Forschung, Entwicklung und Anwendung, Dresden, 6. - 8. Mai 2013, DGZfP-Jahrestagung 2013 Zerst{\"o}rungsfreie Materialpr{\"u}fung}, publisher = {DGZfP}, address = {Berlin}, language = {de} } @inproceedings{WolffKordonHusseinetal., author = {Wolff, Matthias and Kordon, Ulrich and Hussein, Hussein and Eichner, Matthias and Tsch{\"o}pe, Constanze and Hoffmann, R{\"u}diger}, title = {Auscultatory blood pressure measurement using HMMs}, series = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, Hawaii, April 15-20, 2007}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, Hawaii, April 15-20, 2007}, publisher = {IEEE}, doi = {10.1109/ICASSP.2007.366702}, pages = {I-405 -- I-408}, language = {en} } @misc{TschoepeWolffPetersenetal., author = {Tsch{\"o}pe, Constanze and Wolff, Matthias and Petersen, Christer and Buttgereit, David and Kr{\"u}ger, Hauke and Michel, Georg and G{\"o}ring, Elke}, title = {Universal Cognitive User Interface, 27. Konferenz Elektronische Sprachsignalverarbeitung 2016, Leipzig, 02.-04.03.2016 - Postersitzung 1}, address = {Leipzig}, language = {de} } @inproceedings{TschoepeDuckhornBluethgenetal., author = {Tsch{\"o}pe, Constanze and Duckhorn, Frank and Bl{\"u}thgen, Peter and Richter, Christian and Papsdorf, Gunther and Wolff, Matthias}, title = {Miniaturisiertes System zur intelligenten Signalverarbeitung}, series = {DGZFP-Jahrestagung 2017, Zerst{\"o}rungsfreie Materialpr{\"u}fung, Koblenz, 22.-24.05.2017, Kurzfassungen der Vortr{\"a}ge und Posterbeitr{\"a}ge}, booktitle = {DGZFP-Jahrestagung 2017, Zerst{\"o}rungsfreie Materialpr{\"u}fung, Koblenz, 22.-24.05.2017, Kurzfassungen der Vortr{\"a}ge und Posterbeitr{\"a}ge}, publisher = {DGZIP}, address = {Berlin}, pages = {S. 192}, language = {de} } @techreport{TschoepeDuckhornWolff, author = {Tsch{\"o}pe, Constanze and Duckhorn, Frank and Wolff, Matthias}, title = {Akustische Mustererkennung: Qualit{\"a}tskontrolle - Vorausschauende Instandhaltung - Zustands{\"u}berwachung}, publisher = {Fraunhofer-IKTS}, address = {Dresden}, pages = {6}, language = {de} } @misc{WolffRoemerTschoepeetal., author = {Wolff, Matthias and R{\"o}mer, Ronald and Tsch{\"o}pe, Constanze and Hentschel, Dieter}, title = {Verfahren und Vorrichtung zur Verhaltenssteuerung von Systemen}, language = {de} } @misc{TschoepeKraljevskiDuckhornetal., author = {Tsch{\"o}pe, Constanze and Kraljevski, Ivan and Duckhorn, Frank and Wolff, Matthias}, title = {Sprachtechnologie und akustische Mustererkennung in der medizinischen Anwendung}, series = {16. Landeskonferenz „Digitalisierung im Gesundheitswesen" 2021}, journal = {16. Landeskonferenz „Digitalisierung im Gesundheitswesen" 2021}, pages = {9}, language = {de} } @misc{WunderlichTschoepeDuckhorn, author = {Wunderlich, Christian and Tsch{\"o}pe, Constanze and Duckhorn, Frank}, title = {Advanced methods in NDE using machine learning approaches}, series = {44th Annual Review of Progress in Quantitative Nondestructive Evaluation, Provo, Utah, USA, 16-21 July 2017}, volume = {37}, journal = {44th Annual Review of Progress in Quantitative Nondestructive Evaluation, Provo, Utah, USA, 16-21 July 2017}, publisher = {AIP Publishing}, address = {College Park, Maryland}, issn = {0094-243X}, doi = {10.1063/1.5031519}, pages = {1 -- 8}, abstract = {Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability prediction based on big data becomes possible, even if components are used in different versions or configurations. This is the promise behind German Industry 4.0.}, language = {en} } @inproceedings{TschoepeHentschelWolffetal., author = {Tsch{\"o}pe, Constanze and Hentschel, Dieter and Wolff, Matthias and Eichner, Matthias and Hoffmann, R{\"u}diger}, title = {Classification of non-speech acoustic signals using structure models}, series = {Proceedings, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 17 - 21, 2004, Montreal, Canada, vol. 5}, volume = {5}, booktitle = {Proceedings, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 17 - 21, 2004, Montreal, Canada, vol. 5}, publisher = {IEEE Operations Center}, address = {Piscataway, NJ}, isbn = {0-7803-8484-9}, doi = {10.1109/ICASSP.2004.1327195}, pages = {653 -- 656}, abstract = {Non-speech acoustic signals are widely used as the input of systems for non-destructive testing. In this rapidly growing field, the signals have an increasing complexity leading to the fact that powerful models are required. Methods like DTW and HMM, which are established in speech recognition, have been successfully used but are not sufficient in all cases. We propose the application of generalized structured Markov graphs (SMG). We describe a task independent structure learning technique which automatically adapts the models to the structure of the test signals. We demonstrate that our solution outperforms hand-tuned HMM structures in terms of class discrimination by two case studies using data from real applications.}, language = {en} } @inproceedings{WolffSchubertHoffmannetal., author = {Wolff, Matthias and Schubert, R. and Hoffmann, R{\"u}diger and Tsch{\"o}pe, Constanze and Schulze, E. and Neun{\"u}bel, H.}, title = {Experiments in Acoustic Structural Health Monitoring of Airplane Parts}, series = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2008), 30.3.-4.4.2008, Las Vegas, USA}, booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2008), 30.3.-4.4.2008, Las Vegas, USA}, publisher = {IEEE}, isbn = {978-1-4244-1483-3}, doi = {10.1109/ICASSP.2008.4518040}, pages = {2037 -- 2040}, language = {en} } @incollection{HoffmannEichnerKordonetal., author = {Hoffmann, R{\"u}diger and Eichner, Matthias and Kordon, Ulrich and Tsch{\"o}pe, Constanze and Wolff, Matthias}, title = {Anwendung von Spracherkennungsalgorithmen auf nichtsprachliche akustische Signale}, series = {Sprachsignalverarbeitung : Analyse und Anwendungen ; zum 65. Geburtstag von Klaus Fellbaum}, booktitle = {Sprachsignalverarbeitung : Analyse und Anwendungen ; zum 65. Geburtstag von Klaus Fellbaum}, editor = {Hentschel, Christian}, publisher = {TUDpress}, address = {Dresden}, isbn = {978-3-940046-02-4}, pages = {46 -- 57}, language = {de} } @inproceedings{StrechaWolffDuckhornetal., author = {Strecha, Guntram and Wolff, Matthias and Duckhorn, Frank and Wittenberg, S{\"o}ren and Tsch{\"o}pe, Constanze}, title = {The HMM synthesis algorithm of an embedded unified speech recognizer and synthesizer}, series = {Proceedings of the Annual Conference of the International Speech Communication Association 2009, Interspeech 2009, 6 - 10 September, 2009, Brighton, UK}, booktitle = {Proceedings of the Annual Conference of the International Speech Communication Association 2009, Interspeech 2009, 6 - 10 September, 2009, Brighton, UK}, publisher = {ISCA}, address = {Brighton}, pages = {1763 -- 1766}, language = {en} } @misc{PuschCherifFarooqetal., author = {Pusch, T. and Cherif, Chokri and Farooq, Aamir and Wittenberg, S{\"o}ren and Wolff, Matthias and Hoffmann, R{\"u}diger and Tsch{\"o}pe, Constanze}, title = {Fehlerfr{\"u}herkennung an Textilmaschinen mit Hilfe der K{\"o}rperschallanalyse}, series = {Melliand Textilberichte}, volume = {90}, journal = {Melliand Textilberichte}, number = {3}, issn = {0341-0781}, pages = {113 -- 115}, language = {de} } @inproceedings{WolffTschoepe, author = {Wolff, Matthias and Tsch{\"o}pe, Constanze}, title = {Pattern recognition for sensor signals}, series = {Proceedings of the IEEE Sensors Conference 2009, Christchurch, New Zealand, 25 - 28 October 2009}, booktitle = {Proceedings of the IEEE Sensors Conference 2009, Christchurch, New Zealand, 25 - 28 October 2009}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-424-44548-6}, doi = {10.1109/ICSENS.2009.5398338}, pages = {665 -- 668}, language = {en} } @misc{LiKraljevskiMeyeretal., author = {Li, Huajian and Kraljevski, Ivan and Meyer, Paul and Tsch{\"o}pe, Constanze and Wolff, Matthias}, title = {YOLO-ICP : deep learning integrated pose estimation for bin-picking of multiple objects}, series = {2024 IEEE SENSORS, Proceedings, Kobe, Japan, 2024}, journal = {2024 IEEE SENSORS, Proceedings, Kobe, Japan, 2024}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, address = {Piscataway, New Jersey}, isbn = {979-8-3503-6351-7}, doi = {10.1109/SENSORS60989.2024.10784539}, pages = {1 -- 4}, abstract = {In this paper, we present a novel deep learning-integrated pipeline called YOLO-ICP that aims to estimate the six degree of freedom (6-DoF) pose of objects using RGB-D sensors and does not require pose labels to train deep learning networks. YOLO-ICP integrates a real-time object detection algorithm with a point cloud registration method to estimate the pose of multiple objects. We evaluated our approach by quantitatively comparing it with baseline models on the OccludedLINEMOD dataset. Experimental results illustrate that our approach outperforms baseline models in challenging scenarios with textureless and occluded objects. In particular, our pipeline shows superior performance when dealing with small and symmetric objects in terms of the ADD(-S) metric.}, language = {en} } @misc{SchmidtHildebrandKraljevskietal., author = {Schmidt, Ralph Rudi and Hildebrand, Jorg and Kraljevski, Ivan and Duckhorn, Frank and Tsch{\"o}pe, Constanze}, title = {A study for laser additive manufacturing quality and material classification using machine learning}, series = {2022 IEEE sensors}, journal = {2022 IEEE sensors}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, address = {Piscataway, New Jersey}, isbn = {978-1-6654-8464-0}, issn = {2168-9229}, doi = {10.1109/SENSORS52175.2022.9967311}, pages = {1 -- 4}, abstract = {This paper demonstrates the use of acoustic emissions (AEs) to monitor the quality, and material used, for the laser additive manufacturing (LAM) process with steel and copper wire. Layers of deposited material (steel or copper) were created using LAM. The quality of these layers was either good or unstable. The AEs were recorded using three sensors, one microphone, and two structure-borne sound probes. The recorded signals were processed and transformed using the fast Fourier method. Then models were trained with the processed data and evaluated using a fivefold cross-validation. Results show that it is possible to accurately classify the materials used during LAM (up to a balanced accuracy [BAcc] score of 0.99). Also, the process quality could be classified with a BAcc score of up to 0.81. Overall, the results are promising, but further research and data collection are necessary for a proper validation of our results.}, language = {en} } @misc{OpitzWunderlichBendjusetal., author = {Opitz, Joerg and Wunderlich, Christian and Bendjus, B. and Cikalova, U. and Wolf, C. and Naumann, S. and Lehmann, A. and Barth, M. and Duckhorn, Frank and K{\"o}hler, B. and Tsch{\"o}ke, K. and Windisch, T. and Tsch{\"o}pe, Constanze and Moritz, T. and Scheithauer, U.}, title = {Materialdiagnose und integrale Pr{\"u}fverfahren f{\"u}r keramische Bauteile}, series = {Keramische Zeitschrift}, volume = {68}, journal = {Keramische Zeitschrift}, number = {4-5}, publisher = {Springer Science and Business Media LLC}, address = {Berlin ; Heidelberg}, issn = {0023-0561}, doi = {10.1007/BF03400267}, pages = {249 -- 254}, abstract = {Hochleistungskeramiken findet man heute h{\"a}ufig als kritische Komponente in neuentwickelten Systemen f{\"u}r Zukunftsanwendungen. Die Zuverl{\"a}ssigkeit des gesamten Systems basiert hierbei oft auf der kritischen keramischen Komponente. F{\"u}r diese oft neuentwickelten keramischen Materialien werden neue Methoden f{\"u}r die Prozesssteuerung, Materialdiagnostik und Struktur{\"u}berwachung ben{\"o}tigt. In diesem Artikel werden drei f{\"u}r die Keramikcharakterisierung am Fraunhofer-Institut f{\"u}r Keramische Technologien und Systeme IKTS weiter entwickelte Technologien und Verfahren beschrieben und deren Einsatz anhand von Beispielen illustriert. Dazu werden die Laser-Speckle-Photometrie, die optische Koh{\"a}renztomographie und die Klanganalyse in Kombination mit einer entsprechenden akustischen Mustererkennung als leistungsf{\"a}hige Verfahren f{\"u}r die Materialdiagnostik im Bereich der keramischen Materialien vorgestellt.}, language = {de} }