Learning to Become an Expert: Deep Networks Applied to Super-Resolution Microscopy. - Louis-Émile Robitaille; Audrey Durand; Marc-André Gardner; Christian Gagné 001; Paul De Koninck; Flavie Lavoie-Cardinal (AAAI, 2018)

Rating Super-Resolution Microscopy Images With Deep Learning. - Louis-Émile Robitaille; Audrey Durand; Marc-André Gardner; Christian Gagné 001; Paul De Koninck; Flavie Lavoie-Cardinal (AAAI, 2018)

Annotation Cost-Sensitive Deep Active Learning with Limited Data (Student Abstract). - Renaud Bernatchez; Audrey Durand; Flavie Lavoie-Cardinal (AAAI, 2022)

Contextual bandit optimization of super-resolution microscopy. - Anthony Bilodeau; Renaud Bernatchez; Albert Michaud-Gagnon; Flavie Lavoie-Cardinal; Audrey Durand (Canadian AI, 2022)

Microscopy analysis neural network to solve detection, enumeration and segmentation from image-level annotations. - Anthony Bilodeau; Constantin V. L. Delmas; Martin Parent; Paul De Koninck; Audrey Durand; Flavie Lavoie-Cardinal (Nat. Mach. Intell., 2022)

Filtering Pixel Latent Variables for Unmixing Volumetric Images. - Catherine Bouchard; Vincent Boulanger; Flavie Lavoie-Cardinal; Christian Gagné 001 (CoRR, 2023)

Resolution enhancement with a task-assisted GAN to guide optical nanoscopy image analysis and acquisition. - Catherine Bouchard; Theresa Wiesner; Andréanne Deschênes; Anthony Bilodeau; Benoît Turcotte; Christian Gagné 001; Flavie Lavoie-Cardinal (Nat. Mac. Intell., 2023)

Development of AI-assisted microscopy frameworks through realistic simulation with pySTED. - Anthony Bilodeau; Albert Michaud-Gagnon; Julia Chabbert; Benoît Turcotte; Jörn Heine; Audrey Durand; Flavie Lavoie-Cardinal (Nat. Mac. Intell., 2024)