Gerhard Klassen
Gerhard Klassen
PhD Student in Computer Science
Verified email at cs.uni-duesseldorf.de - Homepage
Title
Cited by
Cited by
Year
Show me your friends and i’ll tell you who you are. finding anomalous time series by conspicuous cluster transitions
M Tatusch, G Klassen, M Bravidor, S Conrad
Australasian Conference on Data Mining, 91-103, 2019
62019
Feature-Based Approach for Severity Scoring of Lung Tuberculosis from CT Images.
K Bogomasov, L Himmelspach, G Klassen, M Tatusch, S Conrad
CLEF (Working Notes), 2018
52018
Fuzzy clustering stability evaluation of time series
G Klassen, M Tatusch, L Himmelspach, S Conrad
International Conference on Information Processing and Management of …, 2020
32020
Behave or Be Detected! Identifying Outlier Sequences by Their Group Cohesion
M Tatusch, G Klassen, S Conrad
International Conference on Big Data Analytics and Knowledge Discovery, 333-347, 2020
12020
Evaluating Machine Learning Algorithms in Predicting Financial Restatements
G Klassen, M Tatusch, W Huo, S Conrad
2020 The 4th International Conference on Business and Information Management …, 2020
12020
How is your team spirit? cluster over-time stability evaluation
M Tatusch, G Klassen, M Bravidor, S Conrad
Machine Learning and Data Mining in Pattern Recognition, MLDM, 2020
12020
Clustering of Time Series Regarding Their Over-Time Stability
G Klassen, M Tatusch, S Conrad
2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1051-1058, 2020
2020
Loners Stand Out. Identification of Anomalous Subsequences Based on Group Performance
M Tatusch, G Klassen, S Conrad
International Conference on Advanced Data Mining and Applications, 360-369, 2020
2020
Predicting Erroneous Financial Statements Using a Density-Based Clustering Approach
M Tatusch, G Klassen, M Bravidor, S Conrad
2020 The 4th International Conference on Business and Information Management …, 2020
2020
Detection and Implicit Classification of Outliers via Different Feature Sets in Polygonal Chains
M Singhof, G Klassen, D Braun, S Conrad
Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017
2017
Anwendungsgebiete für die automatisierte Informationsgewinnung aus Bildern
S Conrad, M Tatusch, K Bogomasov, G Klassen
Episteme in Bewegung, 85, 0
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