bachelor-thesis/sources.bib

%! 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},
}

@misc{caml_paper,
      title={Context-Aware Meta-Learning},
      author={Christopher Fifty and Dennis Duan and Ronald G. Junkins and Ehsan Amid and Jure Leskovec and Christopher Re and Sebastian Thrun},
      year={2024},
      eprint={2310.10971},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2310.10971},
}


@misc{handsonaiI,
    author        = {Andreas Schörgenhumer, Bernhard Schäfl, Michael Widrich},
    title         = {Lecture notes in Hands On AI I, Unit 4 \& 5},
    month         = {October},
    year          = {2021},
    publisher={Johannes Kepler Universität Linz}
}

@misc{pmfpaper,
      title={Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference},
      author={Shell Xu Hu and Da Li and Jan Stühmer and Minyoung Kim and Timothy M. Hospedales},
      year={2022},
      eprint={2204.07305},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2204.07305},
}

@misc{peng2023sgvaclipsemanticguidedvisualadapting,
      title={SgVA-CLIP: Semantic-guided Visual Adapting of Vision-Language Models for Few-shot Image Classification},
      author={Fang Peng and Xiaoshan Yang and Linhui Xiao and Yaowei Wang and Changsheng Xu},
      year={2023},
      eprint={2211.16191},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2211.16191},
}

@misc{singh2022transductivedecoupledvariationalinference,
      title={Transductive Decoupled Variational Inference for Few-Shot Classification},
      author={Anuj Singh and Hadi Jamali-Rad},
      year={2022},
      eprint={2208.10559},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2208.10559},
}

@misc{chen2024unifiedanomalysynthesisstrategy,
      title={A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization},
      author={Qiyu Chen and Huiyuan Luo and Chengkan Lv and Zhengtao Zhang},
      year={2024},
      eprint={2407.09359},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2407.09359},
}

@misc{shalam2022selfoptimaltransportfeaturetransform,
      title={The Self-Optimal-Transport Feature Transform},
      author={Daniel Shalam and Simon Korman},
      year={2022},
      eprint={2204.03065},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2204.03065},
}

@misc{parnami2022learningexamplessummaryapproaches,
      title={Learning from Few Examples: A Summary of Approaches to Few-Shot Learning},
      author={Archit Parnami and Minwoo Lee},
      year={2022},
      eprint={2203.04291},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2203.04291},
}

@misc{chowdhury2021fewshotimageclassificationjust,
      title={Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier},
      author={Arkabandhu Chowdhury and Mingchao Jiang and Swarat Chaudhuri and Chris Jermaine},
      year={2021},
      eprint={2101.00562},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2101.00562},
}


@book{analysisrudin,
    title = {Principles of mathematical analysis},
    author = {Walter Rudin},
    isbn = {},
    series = {Mathermatics Series},
    year = {1976},
    publisher = {Mc Graw Hill},
    keywords = {mathematics}
}


@book{dataminingbook,
    title = {Data Mining: Concepts and Techniques},
    author = {Jiawei Han, Micheline Kamber, Jian Pei},
    isbn = {},
    series = {The Morgan Kaufmann Series in Data Management Systems},
    year = {2012},
    publisher = {Morgran Kaufmann},
    keywords = {mathematics}
}

@book{Goodfellow-et-al-2016,
    title={Deep Learning},
    author={Ian Goodfellow and Yoshua Bengio and Aaron Courville},
    publisher={MIT Press},
    note={\url{http://www.deeplearningbook.org}},
    year={2016}
}