Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
作者： Thomas Schlegl , Philipp Seeböck , Sebastian M. Waldstein , Ursula Schmidt-Erfurth , Georg Langs
DOI: 10.1007/978-3-319-59050-9_12
关键词:
摘要: … Here, we perform unsupervised learning to identify anomalies in imaging data as candidates for markers. We propose AnoGAN, a deep convolutional generative adversarial network to …
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