News

Frontiers9mon
DeepCGAN: early Alzheimer's detection with deep convolutional generative adversarial networks
Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder and the most prevailing cause of dementia. AD critically disturbs the daily routine, which usually needs to be detected at its ...
marktechpost1y
Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder Architectures
The encoder processes the input data to form a context, which the decoder then uses to produce the output. This architecture is common in both RNN-based and transformer-based models. Attention ...
inc421y
What Is Encoder-Decoder Architecture? Here’s All You Need to Know
What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...
IEEE1y
PBR-GAN: Imitating Physically-Based Rendering With Generative Adversarial Networks
The two encoders and the image decoder constitute the generator that learns the ... Furthermore, a real dataset is collected to provide realistic information for training GAN architecture. Extensive ...
pcguide1y
Is Stable Diffusion a GAN?
Well, to tell if Stable Diffusion is a GAN ... decoder. Generative Adversarial Networks (GANs), on the other hand, consist of two parts: a generator, which creates new data instances, and a ...
marktechpost2y
A History of Generative AI: From GAN to GPT-4
It differs from traditional Variational AutoEncoders (VAEs) in two ways: the encoder network outputs discrete codes ... BigBiGAN is an extension of the GAN architecture focusing on image generation ...