Machine learning (ML) models have been widely applied to various applications, including
image classification, text generation, audio recognition, and graph data analysis. However …

Generative Adversarial Networks (GANs) have promoted a variety of applications in
computer vision and natural language processing, among others, due to its generative …

In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

Generative artificial intelligence (AI) has emerged as a powerful technology with numerous
applications in various domains. There is a need to identify the requirements and evaluation …

Score-based generative models can produce high quality image samples comparable to
GANs, without requiring adversarial optimization. However, existing training procedures are …

Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …

Recent work has shown that a variety of semantics emerge in the latent space of Generative
Adversarial Networks (GANs) when being trained to synthesize images. However, it is …

In machine learning, the model is not as complicated as possible. Good generalization
ability means that the model not only performs well on the training data set, but also can …