Feature Visualization for Deep Neural Networks
Supervision: Christian Rupprecht, Federico TombariIn 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
| 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 |
| Start: | |
| Finish: | |
| Thesis (optional): | |
| Picture: | |