70 lines
2.3 KiB
BibTeX
70 lines
2.3 KiB
BibTeX
@article{alexnet,
|
|
author = {Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
|
|
journaltitle = {Advances in neural information processing systems},
|
|
pages = {1097--1105},
|
|
title = {ImageNet Classification with Deep Convolutional Networks},
|
|
url = {https://kr.nvidia.com/content/tesla/pdf/machine-learning/imagenet-classification-with-deep-convolutional-nn.pdf},
|
|
urldate = {2021-04-05},
|
|
volume = {25},
|
|
year = {2012}
|
|
}
|
|
|
|
@inproceedings{cars,
|
|
address = {Sydney, Australia},
|
|
author = {Krause, Jonathan and Stark, Michael and Deng, Jia and Fei-Fei, Li},
|
|
booktitle = {4th International IEEE Workshop on 3D Representation and Recognition (3dRR-13)},
|
|
title = {3D Object Representations for Fine-Grained Categorization},
|
|
url = {https://ai.stanford.edu/~jkrause/cars/car_dataset.html},
|
|
urldate = {2021-04-27},
|
|
year = {2013}
|
|
}
|
|
|
|
@misc{cmabridge-cnns,
|
|
author = {Angermueller, Christof and Kendall, Alex},
|
|
organization = {University of Cambridge},
|
|
title = {Convolutional Neural Networks},
|
|
url = {https://cbl.eng.cam.ac.uk/pub/Intranet/MLG/ReadingGroup/cnn_basics.pdf},
|
|
urldate = {2021-05-02},
|
|
year = {2015}
|
|
}
|
|
|
|
@misc{tds-alexnet,
|
|
author = {Alake, Richmond},
|
|
organization = {Towards Data Science},
|
|
title = {What AlexNet Brought To The World Of Deep Learning},
|
|
url = {https://towardsdatascience.com/what-alexnet-brought-to-the-world-of-deep-learning-46c7974b46fc},
|
|
urldate = {2021-05-02},
|
|
year = {2020}
|
|
}
|
|
|
|
@misc{learnopencv-alexnet,
|
|
author = {Nayak, Sunita},
|
|
month = jun,
|
|
organization = {Learn OpenCV},
|
|
title = {Understanding AlexNet},
|
|
url = {https://learnopencv.com/understanding-alexnet},
|
|
urldate = {2021-05-02},
|
|
year = {2018}
|
|
}
|
|
|
|
@misc{tds-lr-schedules,
|
|
author = {Lau, Suki},
|
|
month = jul,
|
|
organization = {Towards Data Science},
|
|
title = {Learning Rate Schedules and Adaptive Learning Rate Methods for Deep Learning},
|
|
url = {https://towardsdatascience.com/learning-rate-schedules-and-adaptive-learning-rate-methods-for-deep-learning-2c8f433990d1},
|
|
urldate = {2021-05-02},
|
|
year = {2017}
|
|
}
|
|
|
|
@misc{glassbox-train-props,
|
|
author = {Draelos, Rachel},
|
|
month = sep,
|
|
organization = {Glass Box},
|
|
title = {Best Use of Train/Val/Test Splits, with Tips for Medical Data},
|
|
url = {https://glassboxmedicine.com/2019/09/15/best-use-of-train-val-test-splits-with-tips-for-medical-data},
|
|
urldate = {2021-05-02},
|
|
year = {2019}
|
|
}
|
|
|