Published May 19, 2019
| Version v1
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Improvement of multimodal images classification based on DSMT using visual saliency model fusion with SVM
Description
Multimodal images carry available information that can be complementary, redundant information, and overcomes the various problems attached to the unimodal classification task, by modeling and combining these information together. Although, this classification gives acceptable classification results, it still does not reach the level of the visual perception model that has a great ability to classify easily observed scene thanks to the powerful mechanism of the human brain.
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