Fred A. Hamprecht - Begrüßung und Laudatio Bernd Jähne
Bernd Jähne - 10 Jahre HCI
Wolfgang Niehsen - HCI Partners from Industry
Katrin Honauer und Karsten Krispin - Auf der Suche nach dem besten Algorithmus: Testdaten und Metriken zur Performanzanalyse in der Bildverarbeitung
Maximilian Diebold - Mehr als Bilder: 3D, Oberflächenorientierung und optische Materialeigenschaften aus Lichtfeldern
Miguel Bautista - Unsupervised Learning of Representations for Human Pose
Jörg Kappes - Probabilistische Graphische Modelle in der Bildverarbeitung: Von der akademischen Forschung zur klinischen Anwendung
Ullrich Köthe - Innovative Mikroskopie trifft maschinelles Lernen: Wie Informatik bei der Entschlüsselung des Lebens hilft
Beatrix Busse - Grußwort
Andreas Dreuw - Grußwort
Hans-Christian Schultz-Coulon - Grußwort
Carsten Rother - Visual Learning meets Natural Science: Opportunitites and Challenges
Visual Learning meets Natural Science: Opportunitites and Challenges
Three things I am known for…
Visual Learning Lab Heidelberg
My personal development
When is Machine Learning useful?
Classical Machine Learning Tasks
Supervised Machine Learning
Image Classification
Outline
Question: I have some prior knowledge about the process … shall and can I use it?
Image Restoration
Image Restoration for Microscopy
Camera Localization
Question: I have a complex task, which I can’t cast into this simple form … what shall I do?
Learning to compare
Reinforcement learning
Reinforcement Learning and Microscopy
Question: It’s very time-consuming to label all training images … what shall I do?
Crowd Sourcing
Simulation
Known Data Distribution
Known Data Distribution for Medicine
Question: Can you explain me what the network is doing internally?
Why Explainable Machine Learning?
Neural Networks Internals
Dreaming Networks
Most important slide