andy
25f73797e3
Affected files: .obsidian/graph.json .obsidian/workspace.json STEM/AI/Neural Networks/Activation Functions.md STEM/AI/Neural Networks/CNN/CNN.md STEM/AI/Neural Networks/CNN/FCN/FCN.md STEM/AI/Neural Networks/CNN/FCN/FlowNet.md STEM/AI/Neural Networks/CNN/FCN/Highway Networks.md STEM/AI/Neural Networks/CNN/FCN/ResNet.md STEM/AI/Neural Networks/CNN/FCN/Skip Connections.md STEM/AI/Neural Networks/CNN/GAN/DC-GAN.md STEM/AI/Neural Networks/CNN/GAN/GAN.md STEM/AI/Neural Networks/CNN/UpConv.md STEM/img/highway-vs-residual.png STEM/img/imagenet-error.png STEM/img/resnet-arch.png STEM/img/resnet-arch2.png STEM/img/skip-connections 1.png STEM/img/upconv-matrix-result.png STEM/img/upconv-matrix-transposed-result.png STEM/img/upconv-matrix.png STEM/img/upconv-transposed-matrix.png STEM/img/upconv.png
918 B
918 B
- Fractionally strided convolution
- Transposed convolution
- Like a deep interpolation
- Convolution with a fractional input stride
- Up-sampling is convolution 'in reverse'
- Not an actual inverse convolution
- For scaling up by a factor of
f- Consider as a convolution of stride
1/f
- Consider as a convolution of stride
- Could specify kernel
- Or learn
- Can have multiple upconv layers
- Separated by Activation Functions#ReLu
- For non-linear up-sampling conv
- Interpolation is linear
!
Convolution Matrix
Normal
!
- Equivalent operation with a flattened input
- Row per kernel location
- Many-to-one operation
!
Understanding transposed convolutions
Transposed
!
- One-to-many
!