IShengFang/SpectralNormalizationKeras
Spectral Normalization for Keras Dense and Convolution Layers
This project offers a simple way to improve the stability and performance of Keras-based Generative Adversarial Networks (GANs). It takes your existing Keras `Dense` and `Convolutional` layers and applies Spectral Normalization, resulting in higher-quality generated images and more robust training. This is ideal for machine learning researchers and practitioners working on deep learning models for image generation.
121 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher looking to enhance the stability and output quality of your Keras-based Generative Adversarial Networks, especially for image synthesis tasks.
Not ideal if you are working with machine learning models other than GANs or if your primary deep learning framework is not Keras.
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Last pushed
Dec 28, 2019
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