17th International Conference on Pattern Recognition (ICPR'04) - Volume 1 Comparison of Support Vector Machines with Autocorrelation Kernels for Invariant Texture Classification Cambridge UK August 23-August 26 ISBN: 0-7695-2128-2
Support vector machines (SVMs) with autocorrelation kernels are applied to texture classification invariant to similarity transformations and noise. The inner product of autocorrelation functions of an arbitrary order is effectively calculated through the 2nd-order crosscorrelation of original data. Texture classification experiments show that higher performance of SVMs is achieved by exploiting the autocorrelation kernels.
Citation:
Yo Horikawa, "Comparison of Support Vector Machines with Autocorrelation Kernels for Invariant Texture Classification," icpr, vol. 1, pp.660-663, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||