Search alternatives:
codon optimization » wolf optimization (Expand Search)
task optimization » based optimization (Expand Search), phase optimization (Expand Search), path optimization (Expand Search)
binary basic » binary mask (Expand Search)
scoring task » scoring based (Expand Search), cueing task (Expand Search), solving task (Expand Search)
basic codon » basic column (Expand Search)
codon optimization » wolf optimization (Expand Search)
task optimization » based optimization (Expand Search), phase optimization (Expand Search), path optimization (Expand Search)
binary basic » binary mask (Expand Search)
scoring task » scoring based (Expand Search), cueing task (Expand Search), solving task (Expand Search)
basic codon » basic column (Expand Search)
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Sample image for illustration.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Comparison analysis of computation time.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Process flow diagram of CBFD.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Precision recall curve.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Quadratic polynomial in 2D image plane.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Table 1_Creating an interactive database for nasopharyngeal carcinoma management: applying machine learning to evaluate metastasis and survival.docx
Published 2024“…For the survival prediction tasks of OS and CSS, we constructed 45 combinations using nine survival machine learning algorithms. …”