Thesis category: MA thesis

277 to 282 of 571

07MAY 2021
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Invited Talk – Jinwei Zhang (Cornell U): Probabilistic Dipole Inversion for Adaptive Quantitative Susceptibility Mapping, May 11th, 16h CET
Next week, we have the great pleasure to welcome Jinwei Zhang to our lab for a presentation on his latest research. Title: Probabilistic Dipole Inversion for Adaptive Quantitative Susceptibility MappingDate: May 11th, 16h CETLocation: https://fau.zoom.us/j/64677481134 Abstract: A learning-based posterior distribution estimation method, Probabilistic Dipole Inversion (PDI), is proposed to solve the quantitative susceptibility mapping (QSM) inverse […]Next week, we have the great pleasure to welcome Jinwei Zhang to our lab for a presentation on his latest research. Title: Probabilistic Dipole Inversion for Adaptive Quantitative Susceptibility MappingDate: May 11th, 16h CETLocation: https://fau.zoom.us/j/64677481134 Abstract: A learning-based posterior distribution estimation method, Probabilistic Dipole Inversion (PDI), is proposed to solve the quantitative susceptibility mapping (QSM) inverse […]
Read more about Invited Talk – Jinwei Zhang (Cornell U): Probabilistic Dipole Inversion for Adaptive Quantitative Susceptibility Mapping, May 11th, 16h CET
30APR 2021
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Invited Talk – Fabian Isensee (German Cancer Research Center): nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation, May 5th, 10h AM CET
The famous author of the nnU-Net Paper is giving some insights on his most recent discoveries on medical image segmentation at our lab in the next week! Title: nnU-Net: a self-configuring method for deep learning-based biomedical image segmentationDate: May 5th, 10h AM CETLocation: https://fau.zoom.us/j/62043440474 Abstract: Biomedical imaging is a driver of scientific discovery and a […]
Read more about Invited Talk – Fabian Isensee (German Cancer Research Center): nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation, May 5th, 10h AM CET
23APR 2021
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Invited Talk – Petar Veličković (DeepMind) – Geometric Deep Learning: Grids, Graphs, Groups, Geodesics and Gauges, April, 28th 14-16h CET
It’s a great pleasure to welcome Petar Veličković from Deep Mind to our Lab! Title: Geometric Deep Learning: Grids, Graphs, Groups, Geodesics and GaugesLocation: https://fau.zoom.us/j/66759913345Date: April, 28th 14-16h CET Abstract: The last decade has witnessed an experimental revolution in data science and machine learning, epitomised by deep learning methods. Indeed, many high-dimensional learning tasks previously thought […]It’s a great pleasure to welcome Petar Veličković from Deep Mind to our Lab! Title: Geometric Deep Learning: Grids, Graphs, Groups, Geodesics and GaugesLocation: https://fau.zoom.us/j/66759913345Date: April, 28th 14-16h CET Abstract: The last decade has witnessed an experimental revolution in data science and machine learning, epitomised by deep learning methods. Indeed, many high-dimensional learning tasks previously thought […]
Read more about Invited Talk – Petar Veličković (DeepMind) – Geometric Deep Learning: Grids, Graphs, Groups, Geodesics and Gauges, April, 28th 14-16h CET
22APR 2021
News
Invited Talk – Daniel Cremers: Deep Direct Visual SLAM, 26th of April 2021, 14h CET
We welcome Prof. Dr. Daniel Cremers as an invited speaker to our lab next week and are looking forward to his presentation. Title: Deep Direct Visual SLAMDate: 26th of April 2021, 14h CETLocation: https://fau.zoom.us/j/99877083139 Abstract: While neural networks have swept the field of computer vision and replaced classical methods in most areas of image analysis […]
Read more about Invited Talk – Daniel Cremers: Deep Direct Visual SLAM, 26th of April 2021, 14h CET
20APR 2021
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Invited Talk – Luis Pineda (Facebook AI): Active MR k-space Sampling with Reinforcement Learning, April 27th, 16h CET
Next week, our invited speaker is Luis Pineda from Facebook AI Research! Title: Active MR k-space Sampling with Reinforcement LearningDate: April 27th, 16h CETLocation: https://fau.zoom.us/j/69173719446 Abstract: Deep learning approaches have recently shown great promise in accelerating magnetic resonance image (MRI) acquisition. The majority of existing work have focused on designing better reconstruction models given a pre-determined […]Next week, our invited speaker is Luis Pineda from Facebook AI Research! Title: Active MR k-space Sampling with Reinforcement LearningDate: April 27th, 16h CETLocation: https://fau.zoom.us/j/69173719446 Abstract: Deep learning approaches have recently shown great promise in accelerating magnetic resonance image (MRI) acquisition. The majority of existing work have focused on designing better reconstruction models given a pre-determined […]
Read more about Invited Talk – Luis Pineda (Facebook AI): Active MR k-space Sampling with Reinforcement Learning, April 27th, 16h CET
09APR 2021
News
Invited Talk: Prof. Dr. Jochen Hoffmann – Information exchange as an infringement of competition law, April 15th 2021, 12h CET
It’s a great pleasure to announce our next guest in our invited lecture series “Beyond the Patterns”. Guest: Prof. Dr. Jochen Hoffmann, FAU Erlangen-NurembergTitle: Information exchange as an infringement of competition lawDate: April 15th 2021, 12h CETLocation: https://fau.zoom.us/j/69095471924 Abstract: European competition law prohibits the coordination of economic decisions among market participants, esp. price fixing. Information […]It’s a great pleasure to announce our next guest in our invited lecture series “Beyond the Patterns”. Guest: Prof. Dr. Jochen Hoffmann, FAU Erlangen-NurembergTitle: Information exchange as an infringement of competition lawDate: April 15th 2021, 12h CETLocation: https://fau.zoom.us/j/69095471924 Abstract: European competition law prohibits the coordination of economic decisions among market participants, esp. price fixing. Information […]
Read more about Invited Talk: Prof. Dr. Jochen Hoffmann – Information exchange as an infringement of competition law, April 15th 2021, 12h CET