CINECA IRIS Institutional Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishWe 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.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
| Titolo: | Nature Inspiration for Support Vector Machines |
| Autori: | |
| Data di pubblicazione: | 2006 |
| Abstract: | 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. |
| Handle: | http://hdl.handle.net/11567/536345 |
| ISBN: | 9783540465379 9783540465393 |
| Appare nelle tipologie: | 04.01 - Contributo in atti di convegno |
File in questo prodotto:
Copyright © 2020