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Details of competitive CBIR methods.
Details of competitive CBIR methods.
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Figshare
2022-10-03 更新
2026-04-28 收录
基于内容的图像检索
算法性能比较
数据链接:
https://figshare.com/articles/dataset/Details_of_competitive_CBIR_methods_/21264796
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资源简介:
Details of competitive CBIR methods.
应用场景:
创建时间:
2022-10-03
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Retrieval accuracy of 1, 3, 5, 7, and 9 CBIR image retrievals with traditional KNN classification and handcrafted features for each 10-fold.
基于内容的图像检索
图像检索准确率评估
Retrieval accuracy of 1, 3, 5, 7, and 9 CBIR image retrievals with traditional KNN classification and handcrafted features for each 10-fold.
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Comparison with ProMiR .
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算法性能比较
Average distance distributions for the Top Scoring candidates provided by MatureBayes (red) and ProMiR (blue) on a common human/mouse blind test set. The set consisted of 301 miRNA precursors which we
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Specificity values of IRBMO vs. other binary algorithms.
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算法性能比较
Specificity values of IRBMO vs. other binary algorithms.
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A comparison among TPA(FCED), RLA and RLA-CL on simulated data sets (generated with a very high error rate).
数据错误检测
算法性能比较
A comparison among TPA(FCED), RLA and RLA-CL on simulated data sets (generated with a very high error rate).
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Comparisons of median computation times (in seconds) based on 5 runs for the GEM algorithm and the MCMC methods.
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算法性能比较
HMFGraph Gibbs, G-Wishart, and BGGM were run with 5000 iterations. For all p, .
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