Enhanced Active Learning of Convolutional Neural Networks: A Case
               Study for Defect Classification in the Semiconductor Industry

Georgios Koutroulis; Tiago Filipe Teixeira dos Santos; Michael Wiedemann; Christian Faistauer; Roman Kern; Stefan Thalmann

doi:10.5220/0010142902690276

Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry

Georgios Koutroulis^*, Tiago Filipe Teixeira dos Santos, Michael Wiedemann, Christian Faistauer, Roman Kern, Stefan Thalmann

^*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Originalsprache	englisch
Titel	Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020, Volume 1: KDIR, Budapest, Hungary, November 2-4, 2020
DOIs	https://doi.org/10.5220/0010142902690276
Publikationsstatus	Veröffentlicht - 2020

Zugriff auf Dokument

10.5220/0010142902690276

Andere Dateien und Links

https://doi.org/10.5220/0010142902690276

Dieses zitieren

Koutroulis, G., Teixeira dos Santos, T. F., Wiedemann, M., Faistauer, C., Kern, R., & Thalmann, S. (2020). Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry. in Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020, Volume 1: KDIR, Budapest, Hungary, November 2-4, 2020 https://doi.org/10.5220/0010142902690276

Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry. / Koutroulis, Georgios; Teixeira dos Santos, Tiago Filipe; Wiedemann, Michael et al.
Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020, Volume 1: KDIR, Budapest, Hungary, November 2-4, 2020. 2020.

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Koutroulis, G, Teixeira dos Santos, TF, Wiedemann, M, Faistauer, C, Kern, R & Thalmann, S 2020, Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry. in Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020, Volume 1: KDIR, Budapest, Hungary, November 2-4, 2020. https://doi.org/10.5220/0010142902690276

Koutroulis G, Teixeira dos Santos TF, Wiedemann M, Faistauer C, Kern R, Thalmann S. Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry. in Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020, Volume 1: KDIR, Budapest, Hungary, November 2-4, 2020. 2020 doi: 10.5220/0010142902690276

Koutroulis, Georgios ; Teixeira dos Santos, Tiago Filipe ; Wiedemann, Michael et al. / Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry. Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020, Volume 1: KDIR, Budapest, Hungary, November 2-4, 2020. 2020.

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title = "Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry",

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AU - Koutroulis, Georgios

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AU - Faistauer, Christian

AU - Kern, Roman

AU - Thalmann, Stefan

PY - 2020

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DO - 10.5220/0010142902690276

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