Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …

An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …

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 …

Autoencoder is an unsupervised learning model, which can automatically learn data
features from a large number of samples and can act as a dimensionality reduction method …

Existing public face image datasets are strongly biased toward Caucasian faces, and other
races (eg, Latino) are significantly underrepresented. The models trained from such datasets …

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 …

Low fault diagnosis accuracy in case of insufficient and imbalanced samples is a major
problem in the wind turbine fault diagnosis. The imbalance of samples refers to the large …

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 …

Most animal species on Earth are insects, and recent reports suggest that their abundance is
in drastic decline. Although these reports come from a wide range of insect taxa and regions …

Generative artificial intelligence (GAI) has emerged as a rapidly burgeoning field
demonstrating significant potential in creating diverse content intelligently and automatically …