Andre Henriques
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332 lines
10 KiB
BibTeX
332 lines
10 KiB
BibTeX
@online{google-vision-api,
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author ={Google},
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title ={Vision {AI} | Google Cloud},
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year ={2023},
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url ={https://cloud.google.com/vision?hl=en}
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}
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@misc{amazon-rekognition,
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title = {{What Is Amazon Rekognition? (1:42)}},
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journal = {Amazon Web Services, Inc},
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year = {2023},
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month = dec,
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note = {[Online; accessed 18. Dec. 2023]},
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url = {https://aws.amazon.com/rekognition}
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}
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@article{lecun1989handwritten,
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title={Handwritten digit recognition with a back-propagation network},
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author={LeCun, Yann and Boser, Bernhard and Denker, John and Henderson, Donnie and Howard, Richard and Hubbard, Wayne and Jackel, Lawrence},
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journal={Advances in neural information processing systems},
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volume={2},
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year={1989}
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}
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@article{krizhevsky2012imagenet,
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title={Imagenet classification with deep convolutional neural networks},
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author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
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journal={Advances in neural information processing systems},
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volume={25},
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year={2012}
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}
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@article{fukushima1980neocognitron,
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title={Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position},
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author={Fukushima, Kunihiko},
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journal={Biological cybernetics},
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volume={36},
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number={4},
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pages={193--202},
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year={1980},
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publisher={Springer}
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}
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@misc{tensorflow2015-whitepaper,
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title={ {TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
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url={https://www.tensorflow.org/},
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note={Software available from tensorflow.org},
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author={
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Mart\'{i}n~Abadi and
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Ashish~Agarwal and
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Paul~Barham and
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Eugene~Brevdo and
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Zhifeng~Chen and
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Craig~Citro and
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Greg~S.~Corrado and
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Andy~Davis and
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Jeffrey~Dean and
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Matthieu~Devin and
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Sanjay~Ghemawat and
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Ian~Goodfellow and
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Andrew~Harp and
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Geoffrey~Irving and
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Michael~Isard and
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Yangqing Jia and
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Rafal~Jozefowicz and
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Lukasz~Kaiser and
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Manjunath~Kudlur and
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Josh~Levenberg and
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Dandelion~Man\'{e} and
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Rajat~Monga and
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Sherry~Moore and
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Derek~Murray and
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Chris~Olah and
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Mike~Schuster and
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Jonathon~Shlens and
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Benoit~Steiner and
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Ilya~Sutskever and
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Kunal~Talwar and
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Paul~Tucker and
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Vincent~Vanhoucke and
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Vijay~Vasudevan and
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Fernanda~Vi\'{e}gas and
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Oriol~Vinyals and
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Pete~Warden and
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Martin~Wattenberg and
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Martin~Wicke and
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Yuan~Yu and
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Xiaoqiang~Zheng},
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year={2015},
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}
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@misc{chollet2015keras,
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title={Keras},
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author={Chollet, Fran\c{c}ois and others},
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year={2015},
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howpublished={\url{https://keras.io}},
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}
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@misc{htmx,
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title = {{{$<$}/{$>$} htmx - high power tools for html}},
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year = {2023},
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month = nov,
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note = {[Online; accessed 1. Nov. 2023]},
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url = {https://htmx.org}
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}
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@misc{go,
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title = {{The Go Programming Language}},
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year = {2023},
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month = nov,
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note = {[Online; accessed 1. Nov. 2023]},
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url = {https://go.dev}
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}
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@misc{node-to-go,
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title = {{A journey from Node to GoLang}},
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year = {2023},
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month = nov,
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note = {[Online; accessed 5. Nov. 2023]},
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url = {https://www.loginradius.com/blog/engineering/a-journey-from-node-to-golang}
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}
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@misc{amazon-machine-learning,
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title = {{An overview of AI and machine learning services from AWS}},
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journal = {Amazon Web Services, Inc},
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year = {2023},
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month = dec,
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note = {[Online; accessed 18. Dec. 2023]},
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url = {https://aws.amazon.com/machine-learning}
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}
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@misc{amazon-rekognition-custom-labels,
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title = {{What is Amazon Rekognition Custom Labels? - Rekognition}},
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year = {2023},
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month = dec,
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note = {[Online; accessed 18. Dec. 2023]},
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url = {https://docs.aws.amazon.com/rekognition/latest/customlabels-dg/what-is.html?pg=ln&sec=ft}
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}
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@misc{amazon-rekognition-custom-labels-training,
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title = {{Training an Amazon Rekognition Custom Labels model - Rekognition}},
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year = {2023},
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month = dec,
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note = {[Online; accessed 18. Dec. 2023]},
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url = {https://docs.aws.amazon.com/rekognition/latest/customlabels-dg/training-model.html#tm-console}
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}
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@misc{google-vision-price-sheet,
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title = {{Pricing {$\vert$} Vertex AI Vision {$\vert$} Google Cloud}},
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journal = {Google Cloud},
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year = {2023},
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month = dec,
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note = {[Online; accessed 20. Dec. 2023]},
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url = {https://cloud.google.com/vision-ai/pricing}
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}
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@misc{google-vision-product-recognizer-guide,
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title = {{Product Recognizer guide}},
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year = {2023},
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month = dec,
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note = {[Online; accessed 20. Dec. 2023]},
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url = {https://cloud.google.com/vision-ai/docs/product-recognizer}
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}
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@article{mnist,
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title={The mnist database of handwritten digit images for machine learning research},
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author={Deng, Li},
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journal={IEEE Signal Processing Magazine},
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volume={29},
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number={6},
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pages={141--142},
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year={2012},
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publisher={IEEE}
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}
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@article{mist-high-accuracy,
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author = {Sanghyeon An and
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Min Jun Lee and
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Sanglee Park and
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Heerin Yang and
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Jungmin So},
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title = {An Ensemble of Simple Convolutional Neural Network Models for {MNIST}
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Digit Recognition},
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journal = {CoRR},
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volume = {abs/2008.10400},
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year = {2020},
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url = {https://arxiv.org/abs/2008.10400},
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eprinttype = {arXiv},
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eprint = {2008.10400},
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timestamp = {Fri, 28 Aug 2020 12:11:44 +0200},
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biburl = {https://dblp.org/rec/journals/corr/abs-2008-10400.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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@article {lecun-98,
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original = "orig/lecun-98.ps.gz",
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author = "LeCun, Y. and Bottou, L. and Bengio, Y. and Haffner, P.",
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title = "Gradient-Based Learning Applied to Document Recognition",
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journal = "Proceedings of the IEEE",
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month = "November",
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volume = "86",
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number = "11",
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pages = "2278-2324",
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year = 1998
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}
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@inproceedings{imagenet,
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title={Imagenet: A large-scale hierarchical image database},
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author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
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booktitle={2009 IEEE conference on computer vision and pattern recognition},
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pages={248--255},
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year={2009},
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organization={Ieee}
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}
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@article{resnet-152,
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author = {Qilong Wang and
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Banggu Wu and
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Pengfei Zhu and
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Peihua Li and
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Wangmeng Zuo and
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Qinghua Hu},
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title = {ECA-Net: Efficient Channel Attention for Deep Convolutional Neural
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Networks},
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journal = {CoRR},
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volume = {abs/1910.03151},
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year = {2019},
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url = {http://arxiv.org/abs/1910.03151},
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eprinttype = {arXiv},
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eprint = {1910.03151},
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timestamp = {Mon, 04 Dec 2023 21:30:01 +0100},
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biburl = {https://dblp.org/rec/journals/corr/abs-1910-03151.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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@article{efficientnet,
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author = {Mingxing Tan and
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Quoc V. Le},
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title = {EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks},
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journal = {CoRR},
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volume = {abs/1905.11946},
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year = {2019},
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url = {http://arxiv.org/abs/1905.11946},
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eprinttype = {arXiv},
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eprint = {1905.11946},
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timestamp = {Mon, 03 Jun 2019 13:42:33 +0200},
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biburl = {https://dblp.org/rec/journals/corr/abs-1905-11946.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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@misc{resnet,
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title={Deep Residual Learning for Image Recognition},
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author={Kaiming He and Xiangyu Zhang and Shaoqing Ren and Jian Sun},
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year={2015},
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eprint={1512.03385},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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@misc{going-deeper-with-convolutions,
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title={Going Deeper with Convolutions},
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author={Christian Szegedy and Wei Liu and Yangqing Jia and Pierre Sermanet and Scott Reed and Dragomir Anguelov and Dumitru Erhan and Vincent Vanhoucke and Andrew Rabinovich},
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year={2014},
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eprint={1409.4842},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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@misc{very-deep-convolution-networks-for-large-scale-image-recognition,
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title={Very Deep Convolutional Networks for Large-Scale Image Recognition},
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author={Karen Simonyan and Andrew Zisserman},
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year={2015},
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eprint={1409.1556},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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@misc{efficient-net,
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title={EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks},
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author={Mingxing Tan and Quoc V. Le},
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year={2020},
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eprint={1905.11946},
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archivePrefix={arXiv},
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primaryClass={cs.LG}
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}
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@INPROCEEDINGS{inverted-bottleneck-mobilenet,
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author={Sandler, Mark and Howard, Andrew and Zhu, Menglong and Zhmoginov, Andrey and Chen, Liang-Chieh},
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booktitle={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
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title={MobileNetV2: Inverted Residuals and Linear Bottlenecks},
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year={2018},
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volume={},
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number={},
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pages={4510-4520},
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keywords={Manifolds;Neural networks;Computer architecture;Standards;Computational modeling;Task analysis},
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doi={10.1109/CVPR.2018.00474}
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}
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@article{json-api-usage-stats,
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author = {Hnatyuk, Kolya},
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title = {{130+ API Statistics: Usage, Growth {\&} Security}},
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journal = {MarketSplash},
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year = {2023},
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month = oct,
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publisher = {MarketSplash},
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url = {https://marketsplash.com/api-statistics}
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}
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@misc{svelte,
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title = {{Svelte {\ifmmode\bullet\else\textbullet\fi} Cybernetically enhanced web apps}},
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year = {2024},
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month = mar,
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note = {[Online; accessed 12. Mar. 2024]},
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url = {https://svelte.dev}
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}
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@misc{state-of-js-2022,
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title = {{State of JavaScript 2022: Front-end Frameworks}},
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year = {2023},
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month = nov,
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note = {[Online; accessed 12. Mar. 2024]},
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url = {https://2022.stateofjs.com/en-US/libraries/front-end-frameworks}
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}
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@misc{js-frontend-frameworks-performance,
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title = {{Interactive Results}},
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year = {2024},
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month = mar,
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note = {[Online; accessed 12. Mar. 2024]},
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url = {https://krausest.github.io/js-framework-benchmark/current.html}
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}
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@misc{svelte-kit,
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title = {{SvelteKit {\ifmmode\bullet\else\textbullet\fi} Web development, streamlined}},
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year = {2024},
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month = mar,
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note = {[Online; accessed 12. Mar. 2024]},
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url = {https://kit.svelte.dev}
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}
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@misc{nginx,
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title = {{Advanced Load Balancer, Web Server, {\&} Reverse Proxy - NGINX}},
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journal = {NGINX},
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year = {2024},
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month = feb,
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note = {[Online; accessed 12. Mar. 2024]},
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url = {https://www.nginx.com}
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}
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@article{bycrpt,
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author = {Provos, Niels and Mazieres, David},
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year = {2001},
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month = {03},
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pages = {},
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title = {A Future-Adaptable Password Scheme}
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}
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