New Deep Kernel Learning based Models for Image Classification
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 7
Abstract
Deep learning system is used for solving many problems in different domains but it gives an over-fitting risk when richer representations are increased. In this paper, three different models with different deep multiple kernel learning architectures are proposed and evaluated for the breast cancer classification problem. Discrete Wavelet transform and edge histogram descriptor are used to extract the image features. For image classification purpose, support vector machine with the proposed deep multiple kernel models are used. Also, the span bound is employed for optimizing these models over the dual objective function. Furthermore, the comparison between the performance of the traditional support vector machine which uses only single kernel and the introduced models is worked out that show the efficiency of the experimental results of the proposed models.
Authors and Affiliations
Rabha O. Abd-elsalam, Yasser F. Hassan, Mohamed W. Saleh
Keywords
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- EP ID EP260467
- DOI 10.14569/IJACSA.2017.080755
- Views 106
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