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Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies

Research article (IEEE Transactions on Image Processing, 2022) · cited 16× · AI/ML
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Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies

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Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies is a scholarly article[1].

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Direct Wikidata claims

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APA 4ort.xyz Knowledge Graph. (2026). Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies. Retrieved May 24, 2026, from https://4ort.xyz/entity/stabilizing-adversarially-learned-one-class-novelty-detection-using-pseudo-anomalies
MLA “Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/stabilizing-adversarially-learned-one-class-novelty-detection-using-pseudo-anomalies.
BibTeX @misc{4ortxyz_stabilizing-adversarially-learned-one-class-novelty-detection-using-pseudo-anomalies_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies}}, year = {2026}, url = {https://4ort.xyz/entity/stabilizing-adversarially-learned-one-class-novelty-detection-using-pseudo-anomalies}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies — https://4ort.xyz/entity/stabilizing-adversarially-learned-one-class-novelty-detection-using-pseudo-anomalies (retrieved 2026-05-24)

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