Before the lecture

• Quick glance at the wikipedia page of convolution kernels

The lecture

After the lecture

Emblematic papers about new architectures to read:

• VGG, Simonyan and Zisserman 2014
• Inception, Szegedy et al. CVPR 2015
• ResNet, He et al. ECCV 2016
• EfficientNet, Tan et al. ICML 2019

Other papers worth reading:

• Dropout, Srivastava et al. JMLR 2014
• Batch Normalization, Ioffe et al. ICML 2015

Some blog posts:

• About different architectures that are designed to be fast: 3 Small but Powerful Convolutional Neural Networks
• The alternative to batch normalization: Normalization in Deep Learning