MaDNNFeatureVis

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Feature Visualization for Deep Neural Networks

Supervision: Christian Rupprecht, Federico Tombari

In this project we would like to explore the possibilities to get insight into the inner workings of deep (convolutional) neural networks. For many of our trained models we lack the possibility to understand what the features that were learned look like, or what objects, textures, parts of the image are important to the task. Many works have been proposed in this direction. The project will include study of the state of the art in the field and begin with implementing one or more existing method into our framework. From there, dependent on the scope and the progress, new techniques could be developed.


For further information please contact: Christian Rupprecht

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ProjectForm
Title: Feature Visualization for Deep Neural Networks
Abstract: In this project we would like to explore the possibilities to get insight into the inner workings of deep (convolutional) neural networks. For many of our trained models we lack the possibility to understand what the features that were learned look like, or what objects, textures, parts of the image are important to the task. Many works have been proposed in this direction. The project will include study of the state of the art in the field and begin with implementing one or more existing method into our framework. From there, dependent on the scope and the progress, new techniques could be developed.
Student: Felix Grün
Director: Prof. Nassir Navab
Supervisor: Christian Rupprecht, Federico Tombari
Type: Bachelor Thesis
Area:  
Status: finished
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Finish:  
Thesis (optional):  
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Edit | Attach | Refresh | Diffs | More | Revision r1.4 - 27 Apr 2016 - 07:07 - ChristianRupprecht