AI Workshop: Hands-on with GANs with Deep Convolutional Networks

Table des matières

• Introduction Introduction

  • A quick overview of GANs

    4 m 2 s
• 1. Understanding Convolutional and Pooling Layers 1. Understanding Convolutional and Pooling Layers

  • Course outline and prerequisites

    1 m 24 s
  • (Verrouillé)
    Setting up Google Colab cloud-hosted notebooks

    3 m 46 s
  • (Verrouillé)
    Understanding convolutional neural networks

    6 m 28 s
  • (Verrouillé)
    Transforming a multichannel image to tensor

    4 m 8 s
  • (Verrouillé)
    Applying convolutional and pooling layers

    4 m 4 s
  • (Verrouillé)
    Viewing the effect of different filters

    4 m 26 s
• 3. Training a Discriminator as a Classification Model 3. Training a Discriminator as a Classification Model

  • Types of convolutional layers

    4 m 11 s
  • (Verrouillé)
    Training data for discriminator bad fakes and real images

    4 m 34 s
  • (Verrouillé)
    Loading and transforming training image data

    4 m 55 s
  • (Verrouillé)
    Understanding the discriminator architecture

    7 m 8 s
  • (Verrouillé)
    Training a discriminator on bad fakes

    5 m 58 s
  • (Verrouillé)
    Training data for discriminator good fakes and real images

    3 m 8 s
  • (Verrouillé)
    Training a discriminator on good fakes

    4 m 56 s
• 3. Training a Deep Convolutional GAN 3. Training a Deep Convolutional GAN

  • Generator and discriminator

    1 m 43 s
  • (Verrouillé)
    Deep convolutional GANs (DCGANs)

    6 m 16 s
  • (Verrouillé)
    Setting up data for GAN training

    4 m 8 s
  • (Verrouillé)
    Setting up the generator and discriminator

    6 m 18 s
  • (Verrouillé)
    Output from an untrained generator and discriminator

    2 m 17 s
  • (Verrouillé)
    Setting up the GAN training loop

    7 m 9 s
  • (Verrouillé)
    Viewing GAN training results

    4 m 34 s
• Conclusion Conclusion

  • (Verrouillé)
    Summary and next steps

    42 s