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stem/AI/Neural Networks/CV/Datasets.md
andy 8f0b604256 vault backup: 2023-05-26 18:29:17 
Affected files:
.obsidian/graph.json
.obsidian/workspace-mobile.json
.obsidian/workspace.json
STEM/AI/Neural Networks/Activation Functions.md
STEM/AI/Neural Networks/CNN/CNN.md
STEM/AI/Neural Networks/CNN/Convolutional Layer.md
STEM/AI/Neural Networks/CNN/Examples.md
STEM/AI/Neural Networks/CNN/GAN/CycleGAN.md
STEM/AI/Neural Networks/CNN/GAN/DC-GAN.md
STEM/AI/Neural Networks/CNN/GAN/GAN.md
STEM/AI/Neural Networks/CNN/GAN/StackGAN.md
STEM/AI/Neural Networks/CNN/GAN/cGAN.md
STEM/AI/Neural Networks/CNN/Inception Layer.md
STEM/AI/Neural Networks/CNN/Max Pooling.md
STEM/AI/Neural Networks/CNN/Normalisation.md
STEM/AI/Neural Networks/CV/Data Manipulations.md
STEM/AI/Neural Networks/CV/Datasets.md
STEM/AI/Neural Networks/CV/Filters.md
STEM/AI/Neural Networks/CV/Layer Structure.md
STEM/AI/Neural Networks/Weight Init.md
STEM/img/alexnet.png
STEM/img/cgan-example.png
STEM/img/cgan.png
STEM/img/cnn-cv-layer-arch.png
STEM/img/cnn-descriptor.png
STEM/img/cnn-normalisation.png
STEM/img/code-vector-math-for-control-results.png
STEM/img/cvmfc.png
STEM/img/cyclegan-results.png
STEM/img/cyclegan.png
STEM/img/data-aug.png
STEM/img/data-whitening.png
STEM/img/dc-gan.png
STEM/img/fine-tuning-freezing.png
STEM/img/gabor.png
STEM/img/gan-arch.png
STEM/img/gan-arch2.png
STEM/img/gan-results.png
STEM/img/gan-training-discriminator.png
STEM/img/gan-training-generator.png
STEM/img/googlenet-auxilliary-loss.png
STEM/img/googlenet-inception.png
STEM/img/googlenet.png
STEM/img/icv-pos-neg-examples.png
STEM/img/icv-results.png
STEM/img/inception-layer-arch.png
STEM/img/inception-layer-effect.png
STEM/img/lenet-1989.png
STEM/img/lenet-1998.png
STEM/img/max-pooling.png
STEM/img/stackgan-results.png
STEM/img/stackgan.png
STEM/img/under-over-fitting.png
STEM/img/vgg-arch.png
STEM/img/vgg-spec.png
STEM/img/word2vec.png
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MNIST

  • 70,000 hand-drawn characters from US mail
  • 28x28 images
  • 10 classes (0 through 9)
  • Achieved 99.83%
    • Ciresan et al. 2011

CIFAR-10

  • 60,000 colour images
  • 32x32 images
  • 10 classes
    • Airplane
    • Automobile
    • Bird
    • Cat
    • Deer
    • Dog
    • Frog
    • Horse
    • Ship
    • Truck
  • Achieved 90.7%
    • Wan et al. 2013