andy
dcc57e2c85
Affected files: .obsidian/graph.json .obsidian/workspace-mobile.json .obsidian/workspace.json Gaming/Steam controllers.md History/Britain.md STEM/AI/Neural Networks/CNN/CNN.md STEM/AI/Neural Networks/CNN/FCN/FCN.md STEM/AI/Neural Networks/CNN/FCN/ResNet.md STEM/AI/Neural Networks/CV/Datasets.md STEM/AI/Neural Networks/Properties+Capabilities.md STEM/AI/Neural Networks/Transformers/Attention.md STEM/AI/Properties.md Tattoo/Engineering.md Tattoo/Sources.md Tattoo/img/snake-coil.png Untitled.canvas
42 lines
943 B
Markdown
42 lines
943 B
Markdown
Fully [[Convolution]]al Network
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[[Convolutional Layer|Convolutional]] and [[UpConv|up-convolutional layers]] with [[Activation Functions#ReLu|ReLu]] but no others (pooling)
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- All some sort of Encoder-Decoder
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Contractive → [[UpConv]]
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# Image Segmentation
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- For visual output
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- Previously image $\rightarrow$ vector
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- Additional layers to up-sample representation to an image
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- Up-[[convolution]]al
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- De-[[convolution]]al
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![[fcn-uses.png]]
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![[fcn-arch.png]]
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# Training
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- Rarely from scratch
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- Pre-trained weights
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- Replace final layers
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- [[MLP|FC]] layers
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- White-noise initialised
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- Add [[upconv]] layer(s)
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- Fine-tune train
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- Freeze others
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- Annotated GT images
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- Can use summed per-pixel log [[Deep Learning#Loss Function|loss]]
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# Evaluation
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![[fcn-eval.png]]
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- SDS
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- Classical method
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- 52% mAP
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- FCN
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- 62% mAP
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- Intersection over Union
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- IOU
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- Jaccard
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- Averaged over all images
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- $J(A,B)=\frac{|A\cap B|}{|A\cup B|}$ |