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David Muhr
David Muhr
Research Associate
Bestätigte E-Mail-Adresse bei fh-ooe.at - Startseite
Titel
Zitiert von
Zitiert von
Jahr
stopwords: Multilingual stopword lists
K Benoit, D Muhr, K Watanabe
R package version 1, 2019
52*2019
Ensuring the robustness and reliability of data-driven knowledge discovery models in production and manufacturing
S Tripathi, D Muhr, M Brunner, H Jodlbauer, M Dehmer, F Emmert-Streib
Frontiers in artificial intelligence 4, 22, 2021
132021
Large scale predictability analysis of process variables from injection molding machines
S Tripathi, C Mittermayr, D Muhr, H Jodlbauer
Procedia Computer Science 180, 545-560, 2021
52021
Divide and conquer anomaly detection: A case study predicting defective engines
D Muhr, S Tripathi, H Jodlbauer
Procedia Manufacturing 42, 57-61, 2020
42020
An adaptive machine learning methodology to determine manufacturing process parameters for each part
D Muhr, S Tripathi, H Jodlbauer
Procedia Computer Science 180, 764-771, 2021
12021
Outlier/Anomaly Detection of Univariate Time Series: A Dataset Collection and Benchmark
D Muhr, M Affenzeller
International Conference on Big Data Analytics and Knowledge Discovery, 163-169, 2022
2022
Hybrid (CPU/GPU) Exact Nearest Neighbors Search in High-Dimensional Spaces
D Muhr, M Affenzeller
IFIP International Conference on Artificial Intelligence Applications and …, 2022
2022
Little data is often enough for distance-based outlier detection
D Muhr, M Affenzeller
Procedia Computer Science 200, 984-992, 2022
2022
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