%! Author = lukas %! Date = 4/9/24 @InProceedings{crossentropy, ISSN = {00359246}, URL = {http://www.jstor.org/stable/2984087}, abstract = {This paper deals first with the relationship between the theory of probability and the theory of rational behaviour. A method is then suggested for encouraging people to make accurate probability estimates, a connection with the theory of information being mentioned. Finally Wald's theory of statistical decision functions is summarised and generalised and its relation to the theory of rational behaviour is discussed.}, author = {I. J. Good}, journal = {Journal of the Royal Statistical Society. Series B (Methodological)}, number = {1}, pages = {107--114}, publisher = {[Royal Statistical Society, Wiley]}, title = {Rational Decisions}, urldate = {2024-05-23}, volume = {14}, year = {1952} } @misc{efficientADpaper, title={EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies}, author={Kilian Batzner and Lars Heckler and Rebecca König}, year={2024}, eprint={2303.14535}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2303.14535}, } @misc{patchcorepaper, title={Towards Total Recall in Industrial Anomaly Detection}, author={Karsten Roth and Latha Pemula and Joaquin Zepeda and Bernhard Schölkopf and Thomas Brox and Peter Gehler}, year={2022}, eprint={2106.08265}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2106.08265}, } @misc{jupyter, author = {}, title = {{Project Jupyter Documentation}}, howpublished = "\url{https://docs.jupyter.org/en/latest/}", year = {2024}, note = "[Online; accessed 13-May-2024]" } @misc{cnnintro, title={An Introduction to Convolutional Neural Networks}, author={Keiron O'Shea and Ryan Nash}, year={2015}, eprint={1511.08458}, archivePrefix={arXiv}, primaryClass={cs.NE} } @misc{cnnarchitectureimg, author = {}, title = {{What are convolutional neural networks?}}, howpublished = "\url{https://cointelegraph.com/explained/what-are-convolutional-neural-networks}", year = {2024}, note = "[Online; accessed 12-April-2024]" } @misc{datasetsampleimg, author = {}, title = {{The MVTec anomaly detection dataset (MVTec AD)}}, howpublished = "\url{https://www.mvtec.com/company/research/datasets/mvtec-ad}", year = {2024}, note = "[Online; accessed 12-April-2024]" } @inproceedings{liang2017soft, title={Soft-margin softmax for deep classification}, author={Liang, Xuezhi and Wang, Xiaobo and Lei, Zhen and Liao, Shengcai and Li, Stan Z}, booktitle={International Conference on Neural Information Processing}, pages={413--421}, year={2017}, organization={Springer} } @inbook{Boltzmann, place = {Cambridge}, series = {Cambridge Library Collection - Physical Sciences}, title = {Studien über das Gleichgewicht der lebendigen Kraft zwischen bewegten materiellen Punkten}, booktitle = {Wissenschaftliche Abhandlungen}, publisher = {Cambridge University Press}, author = {Boltzmann, Ludwig}, editor = {Hasenöhrl, FriedrichEditor}, year = {2012}, pages = {49–96}, collection = {Cambridge Library Collection - Physical Sciences}, key = {value},} @misc{resnet, title={Deep Residual Learning for Image Recognition}, author={Kaiming He and Xiangyu Zhang and Shaoqing Ren and Jian Sun}, year={2015}, eprint={1512.03385}, archivePrefix={arXiv}, primaryClass={cs.CV} } @misc{snell2017prototypicalnetworksfewshotlearning, title={Prototypical Networks for Few-shot Learning}, author={Jake Snell and Kevin Swersky and Richard S. Zemel}, year={2017}, eprint={1703.05175}, archivePrefix={arXiv}, primaryClass={cs.LG}, url={https://arxiv.org/abs/1703.05175}, }