A Comprehensive Survey of Image Augmentation Techniques for Deep Learning

Self-paced Data Augmentation for Training Neural Networks

(2021) Tomoumi Takase et al.   NEUROCOMPUTING

Generative Adversarial Network with Multi-branch Discriminator for imbalanced cross-species image-to-image translation

(2021) Ziqiang Zheng et al.   NEURAL NETWORKS

DRIT++: Diverse Image-to-Image Translation via Disentangled Representations

(2020) Hsin-Ying Lee et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

A survey on face data augmentation for the training of deep neural networks

(2020) Xiang Wang et al.   NEURAL COMPUTING & APPLICATIONS

GridMix: Strong Regularization Through Local Context Mapping

(2020) Kyungjune Baek et al.   PATTERN RECOGNITION

Simplified unsupervised image translation for semantic segmentation adaptation

(2020) Rui Li et al.   PATTERN RECOGNITION

Deep feature augmentation for occluded image classification

(2020) Feng Cen et al.   PATTERN RECOGNITION

MFC-GAN: Class-imbalanced dataset classification using Multiple Fake Class Generative Adversarial Network

(2019) Adamu Ali-Gombe et al.   NEUROCOMPUTING

Toward learning a unified many-to-many mapping for diverse image translation

(2019) Wenju Xu et al.   PATTERN RECOGNITION

MDFN: Multi-scale deep feature learning network for object detection

(2019) Wenchi Ma et al.   PATTERN RECOGNITION

Effective data generation for imbalanced learning using conditional generative adversarial networks

(2018) Georgios Douzas et al.   EXPERT SYSTEMS WITH APPLICATIONS

GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification

(2018) Maayan Frid-Adar et al.   NEUROCOMPUTING

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

Smart Augmentation Learning an Optimal Data Augmentation Strategy

(2017) Joseph Lemley et al.   IEEE Access