bachelor-thesis/experimentalresults.typ
lukas-heilgenbrunner bcbb9bb9de
Some checks failed
Build Typst document / build_typst_documents (push) Failing after 8s
move typst to root and delte latex
2024-11-04 15:11:44 +01:00

16 lines
715 B
XML

= 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?