- AutorIn
- Hedwig Wilhelm
- Titel
- A Neural Network Model of Invariant Object Identification
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa-62050
- Übersetzter Titel (DE)
- Ein Neuronales Netz zur Invarianten Objektidentifikation
- Datum der Einreichung
- 05.07.2010
- Datum der Verteidigung
- 28.10.2010
- Abstract (EN)
- Invariant object recognition is maybe the most basic and fundamental property of our visual system. It is the basis of many other cognitive tasks, like motor actions and social interactions. Hence, the theoretical understanding and modeling of invariant object recognition is one of the central problems in computational neuroscience. Indeed, object recognition consists of two different tasks: classification and identification. The focus of this thesis is on object identification under the basic geometrical transformations shift, scaling, and rotation. The visual system can perform shift, size, and rotation invariant object identification. This thesis consists of two parts. In the first part, we present and investigate the VisNet model proposed by Rolls. The generalization problems of VisNet triggered our development of a new neural network model for invariant object identification. Starting point for an improved generalization behavior is the search for an operation that extracts images features that are invariant under shifts, rotations, and scalings. Extracting invariant features guarantees that an object seen once in a specific pose can be identified in any pose. We present and investigate our model in the second part of this thesis.
- Freie Schlagwörter (DE)
- invariante Objekterkennung, Neuronales Netz, Fourier Transformation
- Freie Schlagwörter (EN)
- invariant object identification, neural network, Fourier transform
- Klassifikation (DDC)
- 000
- GutachterIn
- Prof. Dr. Juergen Jost
- Prof. Dr. Laurenz Wiskott
- BetreuerIn
- Prof. Dr. Juergen Jost
- Den akademischen Grad verleihende / prüfende Institution
- Universität Leipzig, Leipzig
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa-62050
- Veröffentlichungsdatum Qucosa
- 03.11.2010
- Dokumenttyp
- Dissertation
- Sprache des Dokumentes
- Englisch