Fazekas, István and Barta, Attila and Fórián, László (2021) Ensemble noisy label detection on MNIST. Annales Mathematicae et Informaticae, 53. pp. 125-137. ISSN 1787-6117
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Official URL: https://doi.org/10.33039/ami.2021.03.015
Abstract
In this paper machine learning methods are studied for classification data containing some misleading items. We use ensembles of known noise correction methods for preprocessing the training set. Preprocessing can be either relabeling or deleting items detected to have noisy labels. After preprocessing, usual convolutional networks are applied to the data. With preprocessing, the performance of very accurate convolutional networks can be further improved.
Item Type: | Article |
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Uncontrolled Keywords: | Label noise, deep learning, classification |
Subjects: | Q Science / természettudomány > QA Mathematics / matematika > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány |
Depositing User: | Tibor Gál |
Date Deposited: | 25 May 2021 09:00 |
Last Modified: | 03 Apr 2023 07:15 |
URI: | http://real.mtak.hu/id/eprint/125739 |
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