Face-attribute synthesis is a typical application of neural network technology. However, most
current methods suffer from the problem of uncontrollable attribute intensity. In this study, we …

Text-to-image generation has attracted significant interest from researchers and practitioners
in recent years due to its widespread and diverse applications across various industries …

This article proposes a novel deep clustering model based on the variational autoencoder
(VAE), named GamMM-VAE, which can learn latent representations of training data for …

TextToFace is an essential and challenging task in computer vision, which aims to
synthesize realistic images from given description. Most current generative networks tailored …

The small-sample-size issue in hyperspectral image (HSI) classification remains a
significant challenge. To improve the classification accuracy of a dataset with a few labeled …

The current text-to-face synthesis models only utilize text descriptions for image synthesis,
neglecting the prior information of basic facial features. This leads to insufficient learning of …

Medicine is rapidly evolving with the integration of advanced technologies, particularly in
response to user-prompted artificial intelligence (AI). Development of AI algorithms that …

Text-to-image Synthesis is to obtain images with both authenticity and semantic consistency
from natural language descriptions. However, in previous methods, the fusion of semantic …

In recent years, the popular network of adversarial networks has increased in studies for
computer vision. The lack of data usedin the studies and the lack of good training for the …

Modern developments in the fields of natural language processing (NLP) and computer
vision (CV) emphasize the increasing importance of generating images from text …