Publikationen

In: IEEE Access, Vol. 10, Pages 87900-87910, Institute of Electrical and Electronics Engineers (IEEE), 8/2022.

In: Guang Yang; Angelica Aviles-Rivero; Michael Roberts; Carola-Bibiane Schönlieb (Hrsg.). Annual Conference on Medical Image Understanding and Analysis - MIUA 2022. Medical Image Understanding and Analysis (MIUA-2022), July 27-29, Cambridge, United Kingdom, Pages 46-61, LNCS, Vol. 13413, ISBN 978-3-031-12052-7, Springer, Cham, 7/2022.

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In: Sensors - Open Access Journal (Sensors), Vol. 21, Pages 1-16, MDPI, 11/2021.

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In: Applied Sciences, Vol. 10, No. 18 (6460), Pages 1-16, MDPI, 9/2020.

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In: Springer Singapore (Hrsg.). SN Computer Science, Vol. 1, No. Issue 3, Pages 1-16, Springer, Singapore, 5/2020.

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In: Applied Sciences, Vol. 10, No. 7, Pages 1-13, MDPI, 4/2020.

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In: The 28th International Conference on Artificial Neural Networks. International Conference on Artificial Neural Networks (ICANN-2019), September 17-19, Munich, Germany, IEEE, 9/2019.

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In: IEEE (Hrsg.). International Conference on Document Analysis and Recognition. International Conference on Document Analysis and Recognition (ICDAR-2019), located at 15th, September 20-25, Sydney, Australia, IEEE, 2019.

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In: Proceedings - The 15th IAPR International Conference on Document Analysis and Recognition. International Conference on Document Analysis and Recognition (ICDAR-2019), September 20-25, Sydney, Australia, Pages 1397-1402, ISBN 978-1-7281-3015-6, IEEE, 2019.

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In: IEEE Access, Vol. 7, Pages 1991-2005, IEEE, 12/2018.

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Publikationen

Improving Health Mention Classification of Social Media Content using Contrastive Adversarial Training

Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification

TSInsight: A local-global attribution framework for interpretability in time-series data

Fi-Fo Detector: Figure and Formula Detection Using Deformable Networks

Benchmarking Deep Learning Models for Classification of Book Covers

Computer-Aided Diagnosis of Skin Diseases using Deep Neural Networks

DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting

DeepTabStR: Deep Learning based Table Structure Recognition

Rethinking Semantic Segmentation for Table Structure Recognition in Documents

DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series

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