Deep-learning-based models usually require a large amount of data for training, which
guarantees the effectiveness of the trained model. Generative models are no exception, and …

Producing diverse and realistic images with generative models such as GANs typically
requires large scale training with vast amount of images. GANs trained with limited data can …

Auto-Encoder (AE) based neural generative frameworks model the joint-distribution
between the data and the latent space using an Encoder-Decoder pair, with regularization …

Data augmentation for deep learning benefits model training, image transformation, medical
imaging analysis and many other fields. Many existing methods generate new samples from …

Defect classification in the aviation industry plays a crucial role in manufacturing. However,
in non-standardized captured scenes, the object to be inspected and the background are …

Generative models, such as GANs, typically need large-scale training with a substantial
volume of images to generate a variety of realistic images. GANs trained on small dataset …

Producing diverse and realistic images with generative models such as GANs typically
requires large scale training with vast amount of images. GANs trained with extremely …