The Evolution of Convolution Neural Networks
Channel: CodeEmporium
Date: 2018-04-04

From the one that started it all "LeNet" (1998) to the deeper networks we see today like Xception (2017), here are some important CNN architectures you should know. If you like the video, show your support with a like, and SUBSCRIBE for more awesome content on Machine Learning, deep Learning, Data Science and AI


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REFERENCES
[1] LeNet-5 (the start of it all): http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf
[2] Nice Blog post: https://towardsdatascience.com/neural-network-architectures-156e5bad51ba
[3] CNN Architectures: http://slazebni.cs.illinois.edu/spring17/lec01_cnn_architectures.pdf
[4] ImageNet - The data that transformed AI research: https://qz.com/1034972/the-data-that-changed-the-direction-of-ai-research-and-possibly-the-world/
[5]Imagenet (main paper): https://www.researchgate.net/publication/221361415_ImageNet_a_Large-Scale_Hierarchical_Image_Database
[6] AlexNet: https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
[7] Difference between saturating & non-saturating nonlinearities: https://stats.stackexchange.com/questions/174295/what-does-the-term-saturating-nonlinearities-mean
[8] Top-1 accuracy Vs Top-5 Accuracy. What do they mean? https://stats.stackexchange.com/questions/156471/imagenet-what-is-top-1-and-top-5-error-rate
[9] OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks: https://arxiv.org/abs/1312.6229
[10] Network in Network (NiN) Architecture: https://arxiv.org/abs/1312.4400
[11] GoogleNet: https://arxiv.org/pdf/1409.4842.pdf
[12] R-CNN: https://arxiv.org/abs/1311.2524
[13] ResNet: https://arxiv.org/abs/1512.03385
[14] An Overview of ResNet and its Variants: https://towardsdatascience.com/an-overview-of-resnet-and-its-variants-5281e2f56035
[15] Xception: Deep Learning with Depthwise Separable Convolutions: https://arxiv.org/abs/1610.02357