When : 10/04/2017, 11AM
Where : CentraleSupelec, Center for Visual Computing, Conference Room
Host: Pr. Dimitris Samaras
Who : Pr. Pascal Fua, EFPL
What: Domain Adaptation for Microscopy Imaging
Abstract: Electron and Light Microscopy imaging can now deliver high-quality image stacks of neural structures. However, the amount of human annotation effort required to analyze them remains a major bottleneck. While Machine Learning algorithms can be used to help automate this process, they require training data, which is
time-consuming to obtain manually, especially in image stacks. Furthermore, due to changing experimental conditions, successive stacks often exhibit differences that are severe enough to make it difficult to use a classifier trained for a specific one on another. This means that this tedious annotation process has to be repeated for each new stack. In this talk, we will present domain adaptation algorithms that address this issue by effectively leveraging labeled examples across different acquisitions. This drastically reduces the annotation requirements. Our approach can handle complex, non-linear image feature transformations and scales to large microscopy datasets that often involve high-dimensional feature spaces and large 3D data
volumes.
Bio: Pascal Fua received an engineering degree from Ecole Polytechnique, Paris, in 1984 and the Ph.D. degree in Computer Science from the University of Orsay in 1989. He joined EPFL (Swiss Federal Institute of Technology) in 1996 where he is now a Professor in the School of Computer and Communication Science. Before that, he worked at SRI International and at INRIA Sophia-Antipolis as a Computer scientist. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. He has (co)authored over 300 publications in refereed journals and conferences. He is an IEEE Fellow and has been an Associate Editor of IEEE journal Transactions for Pattern Analysis and Machine Intelligence. He often serves as program committee member, area chair, and program chair of major vision conferences and has cofounded two spinoff companies.
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Nikos Paragios, Professor
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@ CentraleSupelec: Professor of Applied Mathematics
@ Institut Universitaire de France: Senior Fellow, Mathematics
@ Elsevier: Editor in Chief, Computer Vision and Image Understanding
@ Inria: Scientific leader, Galen Research Team (Saclay, Ile-de-France)
