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add abstract, finish the alternatvie methods and fix some todos and improve sources
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lukas-heilgenbrunner
2025-01-14 19:22:15 +01:00
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@ -64,7 +64,7 @@ Which is an result that is unexpected (since one can think more samples perform
Clearly all four graphs show that the performance decreases with an increasing number of good samples.
So the conclusion is that the Few-Shot learner should always be trained with as balanced classes as possible.
== How does the 3 (ResNet, CAML, pmf) methods perform in only detecting the anomaly class?
== How does the 3 (ResNet, CAML, P>M>F) 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#todo[Maybe remove comparion?]?_