Generative adversarial networks for anonymous acneic face dataset generation
It is well known that the performance of any classification model is effective if the dataset used for the training process and the test process satisfy some specific requirements. In other words, the more the dataset size is large, balanced, and representative, the more one can trust the proposed m...
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Published in | PloS one Vol. 19; no. 4; p. e0297958 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Public Library of Science (PLoS)
01.01.2024
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Online Access | Get full text |
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