Search Results for author: Saypraseuth Mounsaveng

Found 4 papers, 3 papers with code

Bag of Tricks for Fully Test-Time Adaptation

1 code implementation3 Oct 2023 Saypraseuth Mounsaveng, Florent Chiaroni, Malik Boudiaf, Marco Pedersoli, Ismail Ben Ayed

Fully Test-Time Adaptation (TTA), which aims at adapting models to data drifts, has recently attracted wide interest.

Test-time Adaptation

Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Images

1 code implementation21 Jul 2023 Saypraseuth Mounsaveng, Issam Laradji, David Vázquez, Marco Perdersoli, Ismail Ben Ayed

Experimental results show that our model can learn color and affine transformations that are more helpful to train an image classifier than predefined DA transformations, which are also more expensive as they need to be selected before the training by grid search on a validation set.

Bilevel Optimization Data Augmentation

Adversarial Learning of General Transformations for Data Augmentation

no code implementations ICLR Workshop LLD 2019 Saypraseuth Mounsaveng, David Vazquez, Ismail Ben Ayed, Marco Pedersoli

Data augmentation (DA) is fundamental against overfitting in large convolutional neural networks, especially with a limited training dataset.

Data Augmentation

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