Suggestions for Implementing Specific Generative AI Models in MATLAB

I am deeply interested in the field of generative AI, particularly in models like GANs (Generative Adversarial Networks). I'm looking to implement a simple GAN model for image generation in MATLAB. Could anyone provide specific guidance or best practices on how to design and train a GAN? Any suggestions regarding GAN architectures in MATLAB would also be greatly appreciated.

Thanks:)

Answer 1

[Xianglin]

Implementing a GAN model in MATLAB can be an exciting project. You should start with MATLAB's Deep Learning Toolbox. A typical GAN includes defining a generator and a discriminator network. For the generator, use transposed convolution layers to generate images. The discriminator, on the other hand, can use convolution layers to differentiate between real and generated images. Balancing the training of both networks during the training phase is crucial – they need to compete effectively and improve together. Also, employing the right loss functions and optimizers, like the Adam optimizer, is essential for successful training. MATLAB’s example projects and documentation can provide more specific guidance and code examples to help you get