Published 2006
| Version v1
Publication
Nature Inspiration for Support Vector Machines
- Creators
- ANGUITA, DAVIDE
- D. Sterpi
- Others:
- Anguita, Davide
- D., Sterpi
Description
We propose in this paper a new kernel, suited for Support Vector Machines learning, which is inspired from the biological world. The kernel is based on Gabor filters that are a good model for the response of the cells in the primary visual cortex and have been shown to be very effective in processing natural images. Furthermore, we build a link between energy-efficiency, which is a driving force in biological processing systems, and good generalization ability of learning machines. This connection can be the starting point for developing new kernel-based learning algorithms.
Additional details
- URL
- http://hdl.handle.net/11567/536345
- URN
- urn:oai:iris.unige.it:11567/536345
- Origin repository
- UNIGE