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88 lines
3.4 KiB
BibTeX
88 lines
3.4 KiB
BibTeX
% Encoding: UTF-8
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@Misc{jetsonNano,
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howpublished = {https://developer.nvidia.com/embedded/jetson-nano-developer-kit},
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note = {Accessed: 2022-03-24},
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title = {{Jetson Nano Developer Kit}},
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}
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@Misc{nvidia3070ti,
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howpublished = {https://www.nvidia.com/en-us/geforce/graphics-cards/30-series/rtx-3070-3070ti/},
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note = {Accessed: 2022-03-24},
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title = {{GeForce RTX 3070 Familiy - Specs}},
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}
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@Misc{jetsonNanoTensorFlow,
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howpublished = {https://forums.developer.nvidia.com/t/official-tensorflow-for-jetson-nano/71770},
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note = {Accessed: 2022-03-24},
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title = {{Official TensorFlow for Jetson Nano!}},
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}
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@Misc{opencv,
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howpublished = {https://opencv.org/releases/},
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note = {Accessed: 2022-03-24},
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title = {{OpenCV - releases}},
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}
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@Misc{resnet,
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author = {He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
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title = {Deep Residual Learning for Image Recognition},
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year = {2015},
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copyright = {arXiv.org perpetual, non-exclusive license},
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doi = {10.48550/ARXIV.1512.03385},
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keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences},
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publisher = {arXiv},
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url = {https://arxiv.org/abs/1512.03385},
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}
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@InProceedings{vanishingGradients,
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author = {Tan, Hong Hui and Lim, King Hann},
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booktitle = {2019 7th International Conference on Smart Computing Communications (ICSCC)},
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title = {Vanishing Gradient Mitigation with Deep Learning Neural Network Optimization},
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year = {2019},
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pages = {1-4},
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doi = {10.1109/ICSCC.2019.8843652},
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}
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@Misc{overparameterization,
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author = {Allen-Zhu, Zeyuan and Li, Yuanzhi and Liang, Yingyu},
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title = {Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers},
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year = {2018},
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copyright = {arXiv.org perpetual, non-exclusive license},
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doi = {10.48550/ARXIV.1811.04918},
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keywords = {Machine Learning (cs.LG), Data Structures and Algorithms (cs.DS), Neural and Evolutionary Computing (cs.NE), Optimization and Control (math.OC), Machine Learning (stat.ML), FOS: Computer and information sciences, FOS: Mathematics},
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publisher = {arXiv},
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url = {https://arxiv.org/abs/1811.04918},
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}
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@Misc{autoencoderImg,
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howpublished = {https://en.wikipedia.org/wiki/Autoencoder\#/media/File:Autoencoder\_structure.png},
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note = {Accessed: 2022-03-24},
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title = {{Schematic structure of an autoencoder with 3 fully connected hidden layers. The code (z, or h for reference in the text) is the most internal layer.}},
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}
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@Misc{residualConnectionImg,
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howpublished = {https://i.stack.imgur.com/d9HNk.png},
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note = {Accessed: 2022-03-24},
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title = {{Figure of a residual connection}},
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}
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@Misc{ConvolutionAnimation,
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howpublished = {https://spinkk.github.io/singlekernel\_nopadding.html},
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note = {Accessed: 2022-03-24},
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title = {{Animation of a Convolution}},
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}
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@Article{colorize,
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author = {Zhang, Richard and Isola, Phillip and Efros, Alexei A.},
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title = {Colorful Image Colorization},
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year = {2016},
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copyright = {arXiv.org perpetual, non-exclusive license},
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doi = {10.48550/ARXIV.1603.08511},
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keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
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publisher = {arXiv},
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url = {https://arxiv.org/abs/1603.08511},
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}
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@Comment{jabref-meta: databaseType:bibtex;}
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