Andreas Maier

361 to 191 of 191

10JUL 2020
Lecture Notes in Deep Learning
Lecture Notes in Deep Learning: Loss and Optimization – Part 1
Classification and Regression Losses These are the lecture notes for FAU’s YouTube Lecture “Deep Learning“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were […]
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09JUL 2020
Research Demo Videos
X-Ray Material Decomposition
Authors: Maier, A., Schebesch, F., Syben, C., Würfl, T., Steidl, S., Choi, J. H., & Fahrig, R. In this paper, we consider the use of prior knowledge within neural networks. In particular, we investigate the effect of a known transform within the mapping from input data space to the output domain. We demonstrate that the […]
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09JUL 2020
Lecture Notes in Deep Learning
Lecture Notes in Deep Learning: Feedforward Networks – Part 4
Layer Abstraction These are the lecture notes for FAU’s YouTube Lecture “Deep Learning“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. If […]
Read more about Lecture Notes in Deep Learning: Feedforward Networks – Part 4
08JUL 2020
Lecture Notes in Deep Learning
Lecture Notes in Deep Learning: Feedforward Networks – Part 3
The Backpropagation Algorithm These are the lecture notes for FAU’s YouTube Lecture “Deep Learning“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. […]
Read more about Lecture Notes in Deep Learning: Feedforward Networks – Part 3
07JUL 2020
Research Demo Videos
Browsing through Sealed Historical Manuscripts by using 3-D Computed Tomography with Low-brilliance X-ray Sources
Daniel Stromer, Vincent Christlein, Christine Martindale, Patrick Zippert, Eric Haltenberger, Tino Hausotte & Andreas Maier Severely damaged historical documents are extremely fragile. In many cases, their secrets remain concealed beneath their cover. Recently, non-invasive digitization approaches based on 3-D scanning have demonstrated the ability to recover single pages or letters without the need to open […]Daniel Stromer, Vincent Christlein, Christine Martindale, Patrick Zippert, Eric Haltenberger, Tino Hausotte & Andreas Maier Severely damaged historical documents are extremely fragile. In many cases, their secrets remain concealed beneath their cover. Recently, non-invasive digitization approaches based on 3-D scanning have demonstrated the ability to recover single pages or letters without the need to open […]
Read more about Browsing through Sealed Historical Manuscripts by using 3-D Computed Tomography with Low-brilliance X-ray Sources
07JUL 2020
Lecture Notes in Deep Learning
Lecture Notes in Deep Learning: Feedforward Networks – Part 2
How can Networks actually be trained? These are the lecture notes for FAU’s YouTube Lecture “Deep Learning“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual […]
Read more about Lecture Notes in Deep Learning: Feedforward Networks – Part 2