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gan

Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.

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一个用于肺炎图像分类的轻量级ResNet18-SAM模型实现,采用SH-DCGAN生成少类样本数据,解决了数据不平衡的问题,同时结合剪枝策略实现轻量化!MedGAN-ResLite-V2 Released! Stay tuned!❤

  • Updated May 29, 2024
  • Python

This repository contains an implementation of a Deep Convolutional Generative Adversarial Network (DCGAN) trained on the FashionMNIST dataset. The project aims to generate realistic images of clothing items using a GAN architecture. It includes model definitions, training scripts, and visualizations of generated images at various training stages.

  • Updated May 29, 2024
  • Jupyter Notebook

Released June 10, 2014

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deep-learning neural-network