Project 5 Generative Adversarial Network Zhifei Zhang Generative
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Project 5: Generative Adversarial Network Zhifei Zhang
Generative Adversarial Network (GAN) https: //github. com/hindupuravinash/the-gan-zoo
Generative Adversarial Network (GAN)
Generative Adversarial Network (GAN) New components: Transposed convolution, Batch Normalization Binary Classifier: Conv, Leaky Re. LU, FC, Sigmoid https: //github. com/Pramod. Shenoy/GANerations
Transposed Convolution (Deconvolution) Output Stride=1 Pad=Valid Stride=2 Pad=Same Conv Input Output Deconv Input https: //github. com/vdumoulin/conv_arithmetic
Re. LU vs. Leaky Re. LU (LRe. LU) Used in Generator Used in Discriminator
Batch Normalization (BN) Saturation area Zero gradient https: //towardsdatascience. com/batch-normalization-in-neural-networks-
Generative Adversarial Network (GAN) FC, BN, Re. LU Reshape Deconv, tanh/sigmoid Conv (kernel 5 x 5, stride 2) BN, LRe. LU (slope 0. 2) Reshape, FC, sigmoid Deconv (kernel 5 x 5, stride 2) BN, Re. LU https: //github. com/Pramod. Shenoy/GANerations
GAN on MNIST FC, BN, Reshape 100 Deconv BN, Re. LU 7 x 7 x 16 Deconv Tanh/Sigmoid 14 x 8 Generator Conv, BN, LRe. LU 28 x 1 Conv, BN, LRe. LU 14 x 8 7 x 7 x 16 Discriminator Reshape, FC, BN, LRe. LU 256 FC, Sigmoid 1
Conditional GAN on MNIST One-hot label FC, BN, Reshape 100 Deconv BN, Re. LU 7 x 7 x 16 Deconv Tanh/Sigmoid 14 x 8 Generator Conv, BN, Re. LU 28 x 1 Conv, BN, Re. LU 14 x 8 7 x 7 x 16 Discriminator Reshape, FC, BN, Re. LU 256 FC, Sigmoid 1
Tensor. Flow Implementation of GAN Run the demo code: (Linux or Mac. OS) $ git clone https: //github. com/carpedm 20/DCGAN-tensorflow $ cd DCGAN-tensorflow $ pip install tqdm (if you do not have this package) $ python download. py mnist $ python main. py --dataset mnist --input_height=28 --output_height=28 --train
Tensor. Flow Implementation of GAN • Input: z, image, (label) Training: • Network: D, G for epoch • Loss: D, G • Optimizer: D, G for batch Update D Update G
https: //devblogs. nvidia. com/photo-editing-generative-adversarial-networks-1/
Tensor. Flow Implementation of GAN Testing: • Random Generation • Conditional Generation • Interpolation
- Towardsdatascience
- Generative adversarial network
- Quantum generative adversarial learning
- Spectral normalization gan
- Conditional generator
- Unsupervised image to image translation
- Adversarial stakeholders
- The adversarial system
- What is an adversary system
- Hexiangnan
- Pgd
- Neur ips
- Adversarial interview
- Adversarial system law definition
- Adversarial search problems uses