Denoising diffusion models, a class of generative models, have garnered immense interest
lately in various deep-learning problems. A diffusion probabilistic model defines a forward …

Large-scale Artificial General Intelligence (AGI) models, including Large Language Models
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …

Prompt engineering is a critical technique in the field of natural language processing that
involves designing and optimizing the prompts used to input information into models, aiming …

Adapting a segmentation model from a labeled source domain to a target domain, where a
single unlabeled datum is available, is one of the most challenging problems in domain …

Image data augmentation constitutes a critical methodology in modern computer vision
tasks, since it can facilitate towards enhancing the diversity and quality of training datasets; …

Semantic image synthesis, ie, generating images from user-provided semantic label maps,
is an important conditional image generation task as it allows to control both the content as …

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

While hundreds of artificial intelligence (AI) algorithms are now approved or cleared by the
US Food and Drugs Administration (FDA), many studies have shown inconsistent …

Skin diseases are among the most common and widespread diseases affecting people
around the world. Global warming and climate change are the two main factors leading to …

Anomaly detection is a practical and challenging task due to the scarcity of anomaly
samples in industrial inspection. Some existing anomaly detection methods address this …