Emmanuel Moebel

This paper introduces ExoDeepFinder, a deep learning method for detecting dynamic exocytosis events in TIRFM images, showing better performance and adaptability than conventional methods.

The paper develops an automated system for detecting rare chromosomal aberrations in microscopy images using deep learning, sparse representation, and dimensionality reduction, achieving improved performance over existing methods.

This paper explores unsupervised classification of macromolecular complexes in cryo-ET data using transfer learning and deep learning, showing promising results on real data without manual annotation.

This paper introduces DeepFinder, a deep learning method that improves macromolecule identification in 3D cellular cryo-ET data by localizing multiple species with high accuracy.