Speaker: Nuno Garcia.
Abstract: Deep Learning is revolutionizing several industries in many ways, with applications ranging from autonomous driving, robotics, or medical imaging. Such applications usually require deep neural networks to be trained on large datasets, often of multiple data modalities such as RGB, depth, audio, and others. This talk will give an overview of deep learning methods for multimodal data related to computer vision tasks, and address the realistic scenario of missing modalities at test time for recognition tasks.
Bio: Nuno is an Invited Assistant Professor at the Faculty of Sciences of the University of Lisbon. He received his PhD from the University of Genova and was a researcher at the Pattern Analysis and Computer Vision lab in Istituto Italiano di Tecnologia. He was a visiting researcher at Boston University in 2019. He also worked in data analytics at Deloitte and at Miniclip. His research interests are computer vision and machine learning.
