17 citations · 103 across the 24 of their papers we have counts for
5 papers · 1 filter
Revisiting Data Augmentation for Ultrasound Images
Adam Tupper, Christian Gagné
Data augmentation is a widely used and effective technique to improve the generalization performance of deep neural networks. Yet, despite often facing limited data availability wh…
Analyzing Data Augmentation for Medical Images: A Case Study in Ultrasound Images
Adam Tupper, Christian Gagné
Data augmentation is one of the most effective techniques to improve the generalization performance of deep neural networks. Yet, despite often facing limited data availability in…
Unmixing Optical Signals from Undersampled Volumetric Measurements by Filtering the Pixel Latent Variables
Catherine Bouchard, Andréanne Deschênes, Vincent Boulanger +5
The development of signal unmixing algorithms is essential for leveraging multimodal datasets acquired through a wide array of scientific imaging technologies, including hyperspect…
Domain Agnostic Image-to-image Translation using Low-Resolution Conditioning
Mohamed Abid, Arman Afrasiyabi, Ihsen Hedhli +2
Generally, image-to-image translation (i2i) methods aim at learning mappings across domains with the assumption that the images used for translation share content (e.g., pose) but…
A Generative Model for Hallucinating Diverse Versions of Super Resolution Images
Mohamed Abderrahmen Abid, Ihsen Hedhli, Christian Gagné
Traditionally, the main focus of image super-resolution techniques is on recovering the most likely high-quality images from low-quality images, using a one-to-one low- to high-res…