Convolutional Neural Networks

Architectures of convolutional neural networks for image classification in PyTorch

Architectures

VGGNet

Very Deep Convolutional Networks for Large-Scale Image Recognition, 2014

https://arxiv.org/pdf/1409.1556v6.pdf
InceptionNet-v1 (GoogLeNet)

Going Deeper with Convolutions, 2014

https://arxiv.org/pdf/1409.4842v1.pdf
ResNet

Deep Residual Learning for Image Recognition, 2015

https://arxiv.org/pdf/1512.03385v1.pdf
ResNeXt

Aggregated Residual Transformations for Deep Neural Networks, 2016

https://arxiv.org/pdf/1611.05431.pdf
SqueezeNet-v1

SqueezeNet: AlexNet-Level Accuracy with 50x Fewer Parameters and 0.5Mb Model Size, 2016

https://arxiv.org/pdf/1602.07360v4.pdf
DenseNet

Densely Connected Convolutional Networks, 2017

https://arxiv.org/pdf/1608.06993v5.pdf
MobileNet-v1

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications, 2017

https://arxiv.org/pdf/1704.04861v1.pdf
ShuffleNet-v1

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices, 2017

https://arxiv.org/pdf/1707.01083v2.pdf
SE-ResNet and SENet

Squeeze-and-Excitation Networks, 2017

https://arxiv.org/pdf/1709.01507v4.pdf
SK-ResNet and SKNet

Selective Kernel Networks, 2019

https://arxiv.org/pdf/1903.06586v2.pdf