| Autor: |
Nassih B., Ngadi M., Amine A., El-Attar A. |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
Cybernetics and Information Technologies, Vol 18, Iss 2, Pp 89-97 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
1314-4081 |
| DOI: |
10.2478/cait-2018-0030 |
| Popis: |
Feature extraction is an interactive and iterative analysis process of a large dataset of raw data in order to extract meaningful knowledge. In this article, we present a strong descriptor based on the Discrete Cosine Transform (DCT), we show that the new DCT-based Neighboring Support Vector Classifier (DCT-NSVC) provides a better results compared to other algorithms for supervised classification. Experiments on our real dataset named BOSS, show that the accuracy of classification has reached 99%. The application of DCT-NSVC on MIT-CBCL dataset confirms the performance of the proposed approach. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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