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Applied Mathematics, Computation and Simulation: Part I

Applied Mathematics, Computation and Simulation: Part I

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2:00 pm: PhD Seminars IX

2:00 pm: PhD Seminars - Easter Quiz

Subjects of interest

Archives

Calendar

2:00 pm: PhD Seminars IX

2:00 pm: PhD Seminars - Easter Quiz

Talk 1

Talk 1

Posts tagged "marketing"

admin 2016/11/22 2017/03/21Seminars 0

During last Monday’s seminar, which was the first of the Applied Mathematics chapter, we discovered a lot of things on Mesh adaptations and Fluid Dynamics, thanks to a really wonderful presentation by Eleanore Gauci of team ECUADOR. If you would like to find out more about this work, Eleanore suggests…

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applied mathematics asteroid exploration biological systems brain combinatorial optimization communication conductivity estimation dynamic dynamics EEG fixed point loops fluid dynamics functional emmbeddings fusion plasmas Galerkin time domain methods git health-biology infection spread invariant manifolds mapping marketing mesh modeling nanophotonics networks networks-systems-distributed-computing neuronal cells numerical simulations optimal transport optimisation optimization pattern recognition PDE protein function radar applications regularization retina routing applications scientific dissemination sed shape matching source localization stochastic gradient algorithm variability workshop
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1 2:00 pm: PhD Seminars IX April 1, 2019 2:00 pm – 3:00 pm Talk 1 Speaker Pawel Mlynarski (Epione) Title Deep Learning for Segmentation of Brain Tumors and Organs at Risk Abstract Medical images, such as MRI or CT scans, are used for diagnosis, therapy planning and monitoring of cancers. Automatic segmentation (contouring) of tumors is a very challenging task, due particularly to the variability of tumor shapes, locations and sizes. With their ability to automatically learn relevant features from images, Convolutional Neural Networks have recently achieved state-of-the-art results in a large variety of recognition tasks in medical imaging. However, current deep learning models for tumor segmentation still struggle with important problems such as high computational costs and the lack of annotated training data. In this work, we propose methods based on supervised and semi-supervised deep learning to address these practical challenges. More

15 2:00 pm: PhD Seminars - Easter Quiz April 15, 2019 2:00 pm – 3:00 pm We would like to invite you to an Easter Quiz edition of the PhD Seminars, for an hour of scientific quizzes and exchange. More