Generative adversarial networks (GANs) have recently found applications in image editing.
However, most GAN-based image editing methods often require large-scale datasets with …

Although machine learning models trained on massive data have led to breakthroughs in
several areas, their deployment in privacy-sensitive domains remains limited due to …

Generative data augmentation (GDA) has emerged as a promising technique to alleviate
data scarcity in machine learning applications. This thesis presents a comprehensive survey …

Generative data augmentation (GDA) has emerged as a promising technique to alleviate
data scarcity in machine learning applications. This thesis presents a comprehensive survey …

In the decade, artificial intelligence has achieved great popularity and applications in
medicine and healthcare. Various AI-based algorithms have shown astonishing …

Many recent works on understanding deep learning try to quantify how much individual data
instances influence the optimization and generalization of a model. Such attempts reveal …

Weed management plays an important role in crop yield and quality protection.
Conventional weed control methods largely rely on intensive, blanket herbicide application …

Weed management plays an important role in crop yield and quality protection.
Conventional weed control methods largely rely on herbicide application, which incurs …

With the development of industrial video technology, the use of cameras rather than a variety
of expensive sensors to obtain process or product data has gained more attention. One of …

To capture the relationship between samples and labels, conditional generative models
often inherit spurious correlations from the training dataset. This can result in label …