Small facial image dataset augmentation using conditional GANs based on incomplete edge feature input
Image data collection and labelling is costly or difficult in many real applications. Generating diverse and controllable images using conditional generative adversarial networks (GANs) for data augmentation from a small dataset is promising but challenging as deep convolutional neural networks need...
Guardado en:
Autores principales: | Shih-Kai Hung, John Q. Gan |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/569aead76726429dabfe1c8d961f130f |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Data augmentation using Generative Adversarial Networks (GANs) for GAN-based detection of Pneumonia and COVID-19 in chest X-ray images
por: Saman Motamed, et al.
Publicado: (2021) -
A Multi-Stage GAN for Multi-Organ Chest X-ray Image Generation and Segmentation
por: Giorgio Ciano, et al.
Publicado: (2021) -
Generation of High-Precision Ground Penetrating Radar Images Using Improved Least Square Generative Adversarial Networks
por: Yunpeng Yue, et al.
Publicado: (2021) -
Medical Augmentation (Med-Aug) for Optimal Data Augmentation in Medical Deep Learning Networks
por: Justin Lo, et al.
Publicado: (2021) -
Data Augmentation of Backscatter X-ray Images for Deep Learning-Based Automatic Cargo Inspection
por: Hyunwoo Cho, et al.
Publicado: (2021)