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Panagiotis Gonidakis
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2020 – today
- 2024
- [j2]Luuk H. Boulogne
, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jégou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matías Nicolás Bossa, Abel Díaz Berenguer
The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data. Medical Image Anal. 97: 103230 (2024) - 2023
- [j1]Panagiotis Gonidakis
Handcrafted Features Can Boost Performance and Data-Efficiency for Deep Detection of Lung Nodules From CT Imaging. IEEE Access 11: 126221-126231 (2023) - [i3]Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jégou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data. CoRR abs/2306.10484 (2023) - 2020
- [c2]Panagiotis Gonidakis
Artificially augmenting data or adding more samples? A study on a 3D CNN for lung nodule classification. Computer-Aided Diagnosis 2020 - [c1]Alexander Sóñora-Mengana
Evaluating several ways to combine handcrafted features-based system with a deep learning system using the LUNA16 Challenge framework. Computer-Aided Diagnosis 2020 - [i2]Sofie Tilborghs, Ine Dirks
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients. CoRR abs/2007.15546 (2020) - [i1]Abel Díaz Berenguer
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging. CoRR abs/2011.11719 (2020)
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last updated on 2024-12-10 21:41 CET by the dblp team
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