Convolutional Operations Workshop
Date:
The MLT workshop on CNN Architectures has conducted by our MLT Core Team Engineers Dimitris Katsios, Mustafa Yagmur and Alisher Abdulkhaev.
Part 1: A Historical Review of Deep CNNs
Part 2: Popular CNN Architectures (interactive implementation)
VGG-Net: 3x3 vs 11x11 Convolution
Inception-Net: “1x1 convolution” vs “Fully Connected”
Xception: Separable Convolutions in Inception-Networks
MobileNet: Depthwise (Separable) Convolutions for Training Light Models
ResNet: Residuals in Convolution Operations
DenseNet: Dense Connections in Convolution Operations
SqueezeNet: Distributed Training of Networks
Part 3: Advanced Deep CNN Architectures (short summary only)
ShuffleNet
Squeeze and Excitation Networks (SENet)
Feature Pyramid Networks (FPNs)
Neural ODEs
