"Cross-Year Multi-Modal Image Retrieval Using Siamese Networks" by Margarita Khokhlova, Research Scientist (Post-Doc) at LIRIS Abstract: Alegoria project aims to create content-based image retrieval (CBIR) tools to help end-users accessing great volumes of archive images of French territories which were recently digitized. The difficulty is that many photographic materials are scarcely, or not at all annotated, which makes it hard to link them to modern photographic images of the same territory. In this talk, I am going to present a new custom Siamese architecture for a cross-time multi-modal aerial image retrieval scenario and talk about single-shot and contrastive learning approaches. Speaker biography: Margarita Khokhlova is a postdoc researcher at the IGN Saint-Mande affiliated with LIRIS Lyon. Her primary area of expertise is computer vision. She is currently working on deep learning-based methods for unsupervised multi-modal image description and retrieval. She obtained a Ph.D. degree from the University of Burgundy in 2018, where her dissertation was dedicated to automatic gait analysis using 3D active sensors. She also holds two separate master's degrees. The first is a joint degree in computer vision from the University of Lyon, France and NTNU Norway. The second is in business management administration from the University of Burgundy Dijon. Her research interests include computer vision, deep learning, and data analysis.