Abstract
In this paper, we present a new compactly supported kernel for SVM based image recognition. This kernel which we called Geometric Compactly Supported (GCS) can be viewed as a generalization of spherical kernels to higher dimensions. The construction of the GCS kernel is based on a geometric approach using the intersection volume of two n-dimensional balls. The compactness property of the GCS kernel leads to a sparse Gram matrix which enhances computation efficiency by using sparse linear algebra algorithms. Comparisons of the GCS kernel performance, for image recognition task, with other known kernels prove the interest of this new kernel.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 595-600 |
| Number of pages | 6 |
| Publication status | Published - 1 Dec 2005 |
| Externally published | Yes |
| Event | 15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005 - Warsaw, Poland Duration: 11 Sep 2005 → 15 Sep 2005 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3697 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005 |
|---|---|
| Country | Poland |
| City | Warsaw |
| Period | 11/9/05 → 15/9/05 |
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
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Cite this
Boughorbel, S., Tarel, J. P., Fleuret, F., & Boujemaa, N. (2005). The GCS kernel for SVM-based image recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 595-600). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3697 LNCS).