Lukas Tuggener

Lukas Tuggener
ZHAW
School of Engineering
Forschungsschwerpunkt Information Engineering
Obere Kirchgasse 2 / Steinberggasse 12/14
8400 Winterthur
Persönliches Profil
Tätigkeit an der ZHAW als
Doktorand
tuggeluk.github.io
github.com/tuggeluk
Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse
Data Science, Data Mining, Maschinelles Lernen, Deep Learning, Statistisches Modellieren
Aus- und Fortbildung
Informatikmittelschule, Kantonsschule Büelrain
BSc Wirtschaftsingenieurwesen, ZHAW Winterthur - Vertiefungsrichtung Wirtschaftsmathematik
MSc Statistik, ETH Zürich - Vertiefungsrichtung Computational Statistics
Beruflicher Werdegang
Wissenschaftlicher Assistent, ZHAW - Institut für Datenanalyse und Prozessdesign
Praktikum als Softwareentwickler, UBS
Mitglied in Netzwerken
Projekte
- RealScore - Scanning of Real-World Sheet Music for a Digital Music Stand / Teammitglied / Projekt laufend
- Ada – Advanced Algorithms for an Artificial Data Analyst / Teammitglied / Projekt abgeschlossen
- Libra: A One-Tool Solution for MLD4 Compliance / Teammitglied / Projekt abgeschlossen
- DeepScore: Digitales Notenpult mit musikalischem Verständnis durch Active Sheet Technologie / Teammitglied / Projekt abgeschlossen
Publikationen
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Tuggener, Lukas; Amirian, Mohammadreza ; Benites de Azevedo e Souza, Fernando; von Däniken, Pius ; Gupta, Prakhar; Schilling, Frank-Peter ; Stadelmann, Thilo ,
2020.
Design patterns for resource-constrained automated deep-learning methods .
AI.
1(4),
S. 510-538.
Verfügbar unter : https://doi.org/10.3390/ai1040031
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Tuggener, Lukas; Satyawan, Yvan Putra; Pacha, Alexander; Schmidhuber, Jürgen; Stadelmann, Thilo ,
2020.
The DeepScoresV2 dataset and benchmark for music object detection [ Paper ].
In:
Proceedings of the 25th International Conference on Pattern Recognition 2020 (ICPR’20).
25th International Conference on Pattern Recognition 2020 (ICPR’20), Online, 10-15 January 2021.
IAPR.
Verfügbar unter : https://doi.org/10.21256/zhaw-20647
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Amirian, Mohammadreza ; Tuggener, Lukas; Chavarriaga, Ricardo ; Satyawan, Yvan Putra; Schilling, Frank-Peter ; Schwenker, Friedhelm; Stadelmann, Thilo ,
2020.
Two to trust : AutoML for safe modelling and interpretable deep learning for robustness [ Paper ].
In:
Proceedings of the 1st TAILOR Workshop on Trustworthy AI at ECAI 2020.
1st TAILOR Workshop on Trustworthy AI at ECAI 2020, Santiago de Compostela, Spain, 29-30 August 2020.
Springer.
Verfügbar unter : https://doi.org/10.21256/zhaw-20217
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Tuggener, Lukas; Amirian, Mohammadreza ; Rombach, Katharina; Lörwald, Stefan; Varlet, Anastasia; Westermann, Christian; Stadelmann, Thilo ,
2019.
Automated machine learning in practice : state of the art and recent results [ Paper ].
In:
2019 6th Swiss Conference on Data Science (SDS).
6th Swiss Conference on Data Science (SDS), Bern, 14. Juni 2019.
IEEE.
S. 31-36.
Verfügbar unter : https://doi.org/10.21256/zhaw-3156
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Elezi, Ismail; Tuggener, Lukas; Pelillo, Marcello; Stadelmann, Thilo ,
2018.
DeepScores and Deep Watershed Detection : current state and open issues [ Paper ].
In:
Proceedings of the 1st International Workshop on Reading Music Systems.
1st International Workshop on Reading Music Systems at ISMIR 2018, Paris, France, 20 September 2018.
Paris:
Society for Music Information Retrieval.
S. 13-14.
Verfügbar unter : https://doi.org/10.21256/zhaw-4777
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Stadelmann, Thilo ; Amirian, Mohammadreza ; Arabaci, Ismail; Arnold, Marek; Duivesteijn, Gilbert François; Elezi, Ismail; Geiger, Melanie; Lörwald, Stefan; Meier, Benjamin Bruno; Rombach, Katharina; Tuggener, Lukas,
2018.
Deep learning in the wild [ Paper ].
In:
Proceedings of the 8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR).
8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Siena, Italy, 19-21 September 2018.
IAPR.
Verfügbar unter : https://doi.org/10.21256/zhaw-3872
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Tuggener, Lukas; Elezi, Ismail; Schmidhuber, Jürgen; Stadelmann, Thilo ,
2018.
Deep watershed detector for music object recognition [ Paper ].
In:
Proceedings of the 19th International Society for Music Information Retrieval Conference.
19th International Society for Music Information Retrieval Conference, Paris, 23-27 September 2018.
Paris:
Society for Music Information Retrieval.
Verfügbar unter : https://doi.org/10.21256/zhaw-3760
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Tuggener, Lukas; Elezi, Ismail; Schmidhuber, Jürgen; Pelillo, Marcello; Stadelmann, Thilo ,
2018.
DeepScores : a dataset for segmentation, detection and classification of tiny objects [ Paper ].
In:
Proceedings of the 24th International Conference on Pattern Recognition.
24th International Conference on Pattern Recognition (ICPR 2018), Beijing, China, 20-28 August 2018.
Beijing:
IAPR.
S. 1-6.
Verfügbar unter : https://doi.org/10.21256/zhaw-4255
-
Amirian, Mohammadreza ; Rombach, Katharina; Tuggener, Lukas; Schilling, Frank-Peter ; Stadelmann, Thilo ,
2019.
Efficient deep CNNs for cross-modal automated computer vision under time and space constraints [ Paper ].
In:
ECML-PKDD 2019, Würzburg, Germany, 16-19 September 2019.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Verfügbar unter : https://doi.org/10.21256/zhaw-18357