16 lines
715 B
XML
16 lines
715 B
XML
= Experimental Results
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== Is Few-Shot learning a suitable fit for anomaly detection?
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Should Few-Shot learning be used for anomaly detection tasks?
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How does it compare to well established algorithms such as Patchcore or EfficientAD?
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== How does disbalancing the Shot number affect performance?
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Does giving the Few-Shot learner more good than bad samples improve the model performance?
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== How does the 3 (ResNet, CAML, \pmf) methods perform in only detecting the anomaly class?
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How much does the performance improve if only detecting an anomaly or not?
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How does it compare to PatchCore and EfficientAD?
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== Extra: How does Euclidean distance compare to Cosine-similarity when using ResNet as a feature-extractor?
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