7 citations · 7 across the 4 of their papers we have counts for
4 papers
Bag of Tricks for Fully Test-Time Adaptation
Saypraseuth Mounsaveng, Florent Chiaroni, Malik Boudiaf +2
Fully Test-Time Adaptation (TTA), which aims at adapting models to data drifts, has recently attracted wide interest. Numerous tricks and techniques have been proposed to ensure ro…
Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images
Saypraseuth Mounsaveng, Issam Laradji, David Vázquez +2
Training a deep learning model to classify histopathological images is challenging, because of the color and shape variability of the cells and tissues, and the reduced amount of a…
Learning Data Augmentation with Online Bilevel Optimization for Image Classification
Saypraseuth Mounsaveng, Issam Laradji, Ismail Ben Ayed +2
Data augmentation is a key practice in machine learning for improving generalization performance. However, finding the best data augmentation hyperparameters requires domain knowle…
Adversarial Learning of General Transformations for Data Augmentation
Saypraseuth Mounsaveng, David Vazquez, Ismail Ben Ayed +1
Data augmentation (DA) is fundamental against overfitting in large convolutional neural networks, especially with a limited training dataset. In images, DA is usually based on heur…