Youssef El Habouz

The paper introduces a semi-supervised GAN for cell cycle classification using limited annotated data and unlabelled microscopy images, achieving high accuracy on the Mitocheck dataset.

The Roboscope autonomously captures rare biological events using deep learning and sequence interruption, demonstrating efficiency with minimal training data.

The paper develops a fast image classification method for biological microscopy by selecting discriminant features and using machine learning to improve speed and accuracy.