= Experimental Results

== Is Few-Shot learning a suitable fit for anomaly detection?

Should Few-Shot learning be used for anomaly detection tasks?
How does it compare to well established algorithms such as Patchcore or EfficientAD?

== How does disbalancing the Shot number affect performance?
Does giving the Few-Shot learner more good than bad samples improve the model performance?

== How does the 3 (ResNet, CAML, \pmf) methods perform in only detecting the anomaly class?
How much does the performance improve if only detecting an anomaly or not?
How does it compare to PatchCore and EfficientAD?

== Extra: How does Euclidean distance compare to Cosine-similarity when using ResNet as a feature-extractor?