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Novel Anomaly Detection Scenarios and Evaluation Metrics to Address the Ambiguity in the Definition of Normal Samples
Reiji Saito, Satoshi Kamiya, Kazuhiro Hotta
In conventional anomaly detection, training data consist of only normal samples. However, in real-world scenarios, the definition of a normal sample is often ambiguous. For example…
Genetic Information Analysis of Age-Related Macular Degeneration Fellow Eye Using Multi-Modal Selective ViT
Yoichi Furukawa, Satoshi Kamiya, Yoichi Sakurada +2
In recent years, there has been significant development in the analysis of medical data using machine learning. It is believed that the onset of Age-related Macular Degeneration (A…
Reconstructed Student-Teacher and Discriminative Networks for Anomaly Detection
Shinji Yamada, Satoshi Kamiya, Kazuhiro Hotta
Anomaly detection is an important problem in computer vision; however, the scarcity of anomalous samples makes this task difficult. Thus, recent anomaly detection methods have used…