Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Wörmann, Julian"'
Autor:
Wörmann, Julian, Bogdoll, Daniel, Brunner, Christian, Bührle, Etienne, Chen, Han, Chuo, Evaristus Fuh, Cvejoski, Kostadin, van Elst, Ludger, Gottschall, Philip, Griesche, Stefan, Hellert, Christian, Hesels, Christian, Houben, Sebastian, Joseph, Tim, Keil, Niklas, Kelsch, Johann, Keser, Mert, Königshof, Hendrik, Kraft, Erwin, Kreuser, Leonie, Krone, Kevin, Latka, Tobias, Mattern, Denny, Matthes, Stefan, Motzkus, Franz, Munir, Mohsin, Nekolla, Moritz, Paschke, Adrian, von Pilchau, Stefan Pilar, Pintz, Maximilian Alexander, Qiu, Tianming, Qureishi, Faraz, Rizvi, Syed Tahseen Raza, Reichardt, Jörg, von Rueden, Laura, Sagel, Alexander, Sasdelli, Diogo, Scholl, Tobias, Schunk, Gerhard, Schwalbe, Gesina, Shen, Hao, Shoeb, Youssef, Stapelbroek, Hendrik, Stehr, Vera, Srinivas, Gurucharan, Tran, Anh Tuan, Vivekanandan, Abhishek, Wang, Ya, Wasserrab, Florian, Werner, Tino, Wirth, Christian, Zwicklbauer, Stefan
The availability of representative datasets is an essential prerequisite for many successful artificial intelligence and machine learning models. However, in real life applications these models often encounter scenarios that are inadequately represen
Externí odkaz:
http://arxiv.org/abs/2205.04712
Publikováno v:
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Distance-based dynamic texture recognition is an important research field in multimedia processing with applications ranging from retrieval to segmentation of video data. Based on the conjecture that the most distinctive characteristic of a dynamic t
Externí odkaz:
http://arxiv.org/abs/2102.00841
Autor:
Sagel, Alexander, Sahu, Amit, Matthes, Stefan, Pfeifer, Holger, Qiu, Tianming, Rueß, Harald, Shen, Hao, Wörmann, Julian
Research in machine learning is at a turning point. While supervised deep learning has conquered the field at a breathtaking pace and demonstrated the ability to solve inference problems with unprecedented accuracy, it still does not quite live up to
Externí odkaz:
http://arxiv.org/abs/2012.11406
In the co-sparse analysis model a set of filters is applied to a signal out of the signal class of interest yielding sparse filter responses. As such, it may serve as a prior in inverse problems, or for structural analysis of signals that are known t
Externí odkaz:
http://arxiv.org/abs/1503.02398
The ability of having a sparse representation for a certain class of signals has many applications in data analysis, image processing, and other research fields. Among sparse representations, the cosparse analysis model has recently gained increasing
Externí odkaz:
http://arxiv.org/abs/1406.1621
In this work we address the problem of blindly reconstructing compressively sensed signals by exploiting the co-sparse analysis model. In the analysis model it is assumed that a signal multiplied by an analysis operator results in a sparse vector. We
Externí odkaz:
http://arxiv.org/abs/1302.1094
Publikováno v:
Wörmann, J, Schäler, C, Duchon, M & Schwefel, H-P C 2022, ' Erdschlusslokalisierung basierend auf transienten Spannungsmessungen am Umspannwerk : Erfahrungen aus drei realen Mittelspannungsnetzen ', Paper fremlagt ved Sternpunktbehandlung in Netzen bis 110kV, Esslingen, Tyskland, 11/10/2022-13/10/2022 .
Ein neues datenbasiertes Verfahren zur Lokalisierung von Erdschlussfehlern unter Verwendung transienter Spannungs-messungen am Umspannwerk wird vorgestellt und in realen Mittelspannungsnetzen dreier regionaler Verteilnetzbetreiber validiert. Der Ansa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8d9fbd0111f8fd87fd5f28a8959d365b
https://vbn.aau.dk/da/publications/36889860-5225-4bf1-bc9e-06e9974af040
https://vbn.aau.dk/da/publications/36889860-5225-4bf1-bc9e-06e9974af040
Autor:
Wörmann, Julian
This thesis explores the problem of learning co-sparse analysis operators with separable structures. This model combines the benefits of a reduced computational complexity and an adaptation to the signal class. Additionally, a simultaneous blind lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______518::dbe167323e3699450bd6ffaa8db18ebe
https://mediatum.ub.tum.de/doc/1483047/document.pdf
https://mediatum.ub.tum.de/doc/1483047/document.pdf
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Akademický článek
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