2021 International Conference on Recent Advances in Mathematics and Informatics (ICRAMI) 2021
DOI: 10.1109/icrami52622.2021.9585923
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Histogram Encoding of SIFT Based Visual Words for Target Recognition in Infrared Images

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Cited by 4 publications
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“…Finally, the average accuracy of the feature extraction classifier can reach 93.7%. Nebili et al [10] evaluated a method based on bag of features framework, SIFT, and SVM. The object recognition ability of this method on two types of FLIR data sets is superior to the existing level, and the classification accuracy is increased by 3%.…”
Section: Methods Based On Traditional Image Processingmentioning
confidence: 99%
“…Finally, the average accuracy of the feature extraction classifier can reach 93.7%. Nebili et al [10] evaluated a method based on bag of features framework, SIFT, and SVM. The object recognition ability of this method on two types of FLIR data sets is superior to the existing level, and the classification accuracy is increased by 3%.…”
Section: Methods Based On Traditional Image Processingmentioning
confidence: 99%