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		@@ -22,6 +22,16 @@ Each category comprises a set of defect-free training images and a test set of i
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\subsubsection{Few-Shot Learning}
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					\subsubsection{Few-Shot Learning}
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					\subsubsection{Patchcore}
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					%todo also show values how they perform on MVTec AD
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					\subsubsection{EfficientAD}
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					todo stuff~\cite{patchcorepaper}
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					% https://arxiv.org/pdf/2106.08265
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					todo stuff\cite{efficientADpaper}
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					% https://arxiv.org/pdf/2303.14535
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\subsubsection{Jupyter Notebook}\label{subsubsec:jupyternb}
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					\subsubsection{Jupyter Notebook}\label{subsubsec:jupyternb}
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A Jupyter notebook is a shareable document which combines code and its output, text and visualizations.
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					A Jupyter notebook is a shareable document which combines code and its output, text and visualizations.
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@@ -15,3 +15,23 @@
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    volume = {14},
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					    volume = {14},
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    year = {1952}
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					    year = {1952}
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}
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					}
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					@misc{efficientADpaper,
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					    title={EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies},
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					    author={Kilian Batzner and Lars Heckler and Rebecca König},
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					    year={2024},
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					    eprint={2303.14535},
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					    archivePrefix={arXiv},
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					    primaryClass={cs.CV},
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					    url={https://arxiv.org/abs/2303.14535},
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					}
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					@misc{patchcorepaper,
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					    title={Towards Total Recall in Industrial Anomaly Detection},
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					    author={Karsten Roth and Latha Pemula and Joaquin Zepeda and Bernhard Schölkopf and Thomas Brox and Peter Gehler},
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					    year={2022},
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					    eprint={2106.08265},
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					    archivePrefix={arXiv},
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					    primaryClass={cs.CV},
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					    url={https://arxiv.org/abs/2106.08265},
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					}
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