Generative adversarial networks for anonymous acneic face dataset generation
Hazem Zein,
Samer Chantaf,
Régis Fournier
et al.
Abstract: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 model’s effectiveness and, consequently, the obtained results. Unfortunately, large-size anonymous datasets are generally not publicly available in biomedical applications, especially those dealing with pathological … Show more
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