Distinctive Image Features from Scale-Invariant Keypoints
Citations
99 citations
Cites methods from "Distinctive Image Features from Sca..."
...The number of rows representative handcrafted features include Scale-Invariant Feature Transform (SIFT) [48] and Histogram of Oriented Gradients (HOG) [49]....
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...representative handcrafted features include Scale-Invariant Feature Transform (SIFT) [48] and Histogram of Oriented Gradients (HOG) [49]....
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99 citations
Cites methods from "Distinctive Image Features from Sca..."
...In Awad et al. (2013b), the authors applied the Scale-Invariant Feature Transform (SIFT) algorithm, combined with a Random Sample Consensus (RANSAC) algorithm, and in doing so they improved the identification accuracy using the previously collected database....
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...In Sun et al. (2013), the authors used SIFT (Lowe, 1999, 2004; Mikolajczyk and Schmid, 2005) as a feature extractor for identifying bovine animals....
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...Recently, Noviyanto and Arymurthy (2013) presented a study of using SIFT features and SIFT features combined with a refinement technique for improving identification accuracy....
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...Moreover, the extraction time of SIFT features can be drastically reduced by using modern parallel processing techniques (Awad, 2013)....
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99 citations
99 citations
Cites methods from "Distinctive Image Features from Sca..."
...In this paper, densely sampling strategy is employed to detect interest points and scale invariant feature transform [45] is used to describe image patches....
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99 citations
Cites background from "Distinctive Image Features from Sca..."
...Comparedwith hand-crafted features, for example, Local Binary Patterns (LBP) [55] and Scale Invariant Feature Transform (SIFT) [56], which need additional classifiers to solve vision problems [57–59], the CNNs can learn the features and the classifiers jointly and provide superior performance....
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References
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