Zobrazeno 1 - 8
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pro vyhledávání: '"Kolarik, Martin"'
Publikováno v:
2020 43rd International Conference on Telecommunications and Signal Processing (TSP)
The widespread use of Batch Normalization has enabled training deeper neural networks with more stable and faster results. However, the Batch Normalization works best using large batch size during training and as the state-of-the-art segmentation con
Externí odkaz:
http://arxiv.org/abs/2011.11559
We present a novel approach of 2D to 3D transfer learning based on mapping pre-trained 2D convolutional neural network weights into planar 3D kernels. The method is validated by the proposed planar 3D res-u-net network with encoder transferred from t
Externí odkaz:
http://arxiv.org/abs/2011.11557
Akademický článek
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Autor:
Kolarik, Martin
Publikováno v:
Proceedings of the 25st Conference STUDENT EEICT 2019. s. 739-743. ISBN 978-80-214-5735-5
This paper proposes a method for pre-training segmentation neural networks on small datasets using unlabelled training data with added noise. The pre-training process helps the network with initial better weights settings for the training itself and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2852::b671fefcbcbe8d68b5ef767b7c59fc1e
https://hdl.handle.net/11012/186770
https://hdl.handle.net/11012/186770
Akademický článek
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Publikováno v:
AIP Conference Proceedings; 2015, Vol. 1648 Issue 1, p1-4, 4p
Autor:
Kolařík, Martin
The master’s thesis deals with the analysis of casting technology of the selected aluminium casting. It is a casting of a part of CNC milling machine and it is cast by gravity casting into a permanent mold. The defects which are the cause of a high
Externí odkaz:
http://www.nusl.cz/ntk/nusl-401577
Autor:
Kolařík, Martin
Thesis focuses on analysis of contemporary machine learning methods used for text classification based on emotion and testing several deep neural nework architectures. Outcome of this thesis is a neural network architecture, which is tuned for using
Externí odkaz:
http://www.nusl.cz/ntk/nusl-317210