基本模型

Applications - Keras Documentation

• [2015] VGGNet(16/19) [2]

• [2015] GoogleNet [10]

• [2016] Inception-v1/v2/v3 [4]

• [2016] ResNet [3]

• [2017] Xception [1]

• [2017] InceptionResNet-(v1/v2)、Inception-v4 [5]

• [2017] MobileNet [6]

• [2017] DenseNet [7]

• [2017] NASNet [8]

• [2018] MobileNetV2 [9]

Index

• Inception-v1/v2/v3

  • 相关阅读

• Reference

Inception-v1/v2/v3

相关阅读

• 经典网络GoogLeNet(Inception V3)网络的搭建与实现 - CSDN博客

Reference

• [1] [Xception: Deep Learning with Depthwise Separable Convolutions, CVPR 2017.](./Papers/基本模型/[2017].Xception.(CVPR).pdf)

• [2] Very Deep Convolutional Networks for Large-Scale Image Recognition, ICLR 2015.

• [3] Deep Residual Learning for Image Recognition, CVPR 2016.

• [4] Rethinking the Inception Architecture for Computer Vision, CVPR 2016.

• [5] Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning, AAAI 2017.

• [6] MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications, arXiv 2017.

• [7] Densely Connected Convolutional Networks, CVPR 2017.

• [8] Learning Transferable Architectures for Scalable Image Recognition, arXiv 2017.

• [9] MobileNetV2: Inverted Residuals and Linear Bottlenecks, CVPR 2018.