Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
Thomas Schlegl, Philipp Seeböck, Sebastian M. Waldstein, Ursula Schmidt‐Erfurth, Georg Langs
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Citation edge evidence
- MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection→Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco…Legacy edge — source detail unavailable
- Generative adversarial network in medical imaging: A review→Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco…Legacy edge — source detail unavailable
- Causability and explainability of artificial intelligence in medicine→Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco…Legacy edge — source detail unavailable
- Deep Learning for Anomaly Detection: A Review→Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco…Legacy edge — source detail unavailable
- A State-of-the-Art Survey on Deep Learning Theory and Architectures→Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco…Legacy edge — source detail unavailable
- [No title in the source record — Newcastle University ePrints (Newcastle Univesity)]→Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco…Legacy edge — source detail unavailable
- Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco…→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
- Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco…→A review of novelty detectionLegacy edge — source detail unavailable
- MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection→A review of novelty detectionLegacy edge — source detail unavailable
- [No title in the source record — Newcastle University ePrints (Newcastle Univesity)]→A review of novelty detectionLegacy edge — source detail unavailable
- Deep Learning for Anomaly Detection: A Review→MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly DetectionLegacy edge — source detail unavailable
- Deep Learning for Anomaly Detection: A Review→[No title in the source record — Newcastle University ePrints (Newcastle Univesity)]Legacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Adam: A Method for Stochastic Optimization | 2014 | 84,698 |
| A review of novelty detection | 2014 | 1,647 |
What cites it, inside the corpus
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Topics
| Anomaly Detection Techniques and Applications | Computer Science |
| Retinal Imaging and Analysis | Medicine |
| Cell Image Analysis Techniques | Biochemistry, Genetics and Molecular Biology |
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- supports5 author record(s) attached.
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