{"main_file_link":[{"url":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4414320&tag=1"}],"status":"public","date_created":"2019-11-29T13:50:28Z","publication_identifier":{"eisbn":["978-1-4244-1566-3"],"issn":["1551-2541 "],"unknown":["2378-928X "],"isbn":["978-1-4244-1565-6"]},"title":"A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion","year":2007,"type":"conference","user_id":"45673","doi":"10.1109/MLSP.2007.4414320","author":[{"last_name":"Dyck","full_name":"Dyck, Walter","first_name":"Walter"},{"first_name":"Thomas","full_name":"Türke, Thomas","last_name":"Türke"},{"first_name":"Johannes","last_name":"Schaede","full_name":"Schaede, Johannes","id":"2128"},{"id":"1804","last_name":"Lohweg","full_name":"Lohweg, Volker","first_name":"Volker","orcid":"0000-0002-3325-7887"}],"place":"Thessaloniki, Greece","language":[{"iso":"eng"}],"citation":{"mla":"Dyck, Walter, et al. A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion. MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, 2007, p. accepted for publication, doi:10.1109/MLSP.2007.4414320.","bjps":"Dyck W et al. (2007) A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion. Thessaloniki, Greece: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, p. accepted for publication.","chicago":"Dyck, Walter, Thomas Türke, Johannes Schaede, and Volker Lohweg. “A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion,” accepted for publication. Thessaloniki, Greece: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, 2007. https://doi.org/10.1109/MLSP.2007.4414320.","ieee":"W. Dyck, T. Türke, J. Schaede, and V. Lohweg, “A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion,” 2007, p. accepted for publication.","chicago-de":"Dyck, Walter, Thomas Türke, Johannes Schaede und Volker Lohweg. 2007. A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion. In: , accepted for publication. Thessaloniki, Greece: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING. doi:10.1109/MLSP.2007.4414320, .","ama":"Dyck W, Türke T, Schaede J, Lohweg V. A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion. In: Thessaloniki, Greece: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING; 2007:accepted for publication. doi:10.1109/MLSP.2007.4414320","din1505-2-1":"Dyck, Walter ; Türke, Thomas ; Schaede, Johannes ; Lohweg, Volker: A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion. In: . Thessaloniki, Greece : MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, 2007, S. accepted for publication","ufg":"Dyck, Walter et. al. (2007): A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion, in: , Thessaloniki, Greece, S. accepted for publication.","havard":"W. Dyck, T. Türke, J. Schaede, V. Lohweg, A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion, in: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, Thessaloniki, Greece, 2007: p. accepted for publication.","short":"W. Dyck, T. Türke, J. Schaede, V. Lohweg, in: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, Thessaloniki, Greece, 2007, p. accepted for publication.","apa":"Dyck, W., Türke, T., Schaede, J., & Lohweg, V. (2007). A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion (p. accepted for publication). Thessaloniki, Greece: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING. https://doi.org/10.1109/MLSP.2007.4414320","van":"Dyck W, Türke T, Schaede J, Lohweg V. A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion. In Thessaloniki, Greece: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING; 2007. p. accepted for publication."},"page":"accepted for publication","keyword":["Sensor fusion","Inspection","Optical sensors","Printing machinery","Data security","Data analysis","Production","Degradation","Principal component analysis","Karhunen-Loeve transforms"],"publication_status":"published","department":[{"_id":"DEP5023"}],"date_updated":"2023-03-15T13:49:38Z","publisher":"MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING","_id":"2068","abstract":[{"lang":"eng","text":"The production of printing goods is laborious. Furthermore, the print quality, especially in banknotes, must be assured. It is accepted, that print defects are generated because printing parameters, also machine parameters can change unnoticed. Therefore, a combined concept for a multi-sensory learning and classification model based on new adaptive fuzzy-pattern-classifiers for data inspection is proposed. This inspection concept, which combines optical, acoustical and other machine information, comes up with a large amount of data, which leads to multivariate methods for data analysis. Multivariate methods are useful for analysis of large and complex data sets that consist of many variables measured on large numbers of physical data."}]}