Efficient improvement of classification accuracy via selective test-time augmentation

This publication has 9 references indexed in Scilit:

• Explainability of artificial intelligence methods, applications and challenges: A comprehensive survey
  Information Sciences, 2022
• Assessing the impact of data augmentation and a combination of CNNs on leukemia classification
  Information Sciences, 2022
• A comprehensive survey of recent trends in deep learning for digital images augmentation
  Artificial Intelligence Review, 2021
• Rotation-Invariant Wafer Map Pattern Classification With Convolutional Neural Networks
  IEEE Access, 2020
• A survey on Image Data Augmentation for Deep Learning
  Journal of Big Data, 2019
• Neural Style Transfer: A Review
  IEEE Transactions on Visualization and Computer Graphics, 2019
• Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
  Neurocomputing, 2019
• The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
  Scientific Data, 2018
• Neural Network-Based Uncertainty Quantification: A Survey of Methodologies and Applications
  IEEE Access, 2018