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Showing 141 - 160 results of 312 for search '(("element em algorithm") OR ((("data processing algorithm") OR ("image processing algorithm"))))', query time: 0.72s Refine Results
  1. 141
    The comparisons among these SFIC schemes with different accelerating technologies on 512 × 512 image Lena with sparse number 4.

    The comparisons among these SFIC schemes with different accelerating technologies on 512 × 512 image Lena with sparse number 4. by Jianji Wang (1435495)

    Published 2017
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  2. 142
    Three examples to show the advantage of convergence of the proposed FSFIC scheme.

    Three examples to show the advantage of convergence of the proposed FSFIC scheme. by Jianji Wang (1435495)

    Published 2017
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  3. 143
    Metabolomic Analysis and Visualization Engine for LC−MS Data

    Metabolomic Analysis and Visualization Engine for LC−MS Data by Eugene Melamud (62396)

    Published 2010
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  4. 144
    Metabolomic Analysis and Visualization Engine for LC−MS Data

    Metabolomic Analysis and Visualization Engine for LC−MS Data by Eugene Melamud (62396)

    Published 2010
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  5. 145
    Euclidean Distance between the estimated stain matrix and the ground truth.

    Euclidean Distance between the estimated stain matrix and the ground truth. by Najah Alsubaie (3633154)

    Published 2017
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  6. 146
    Stain colour deconvolution results for a colon tissue image.

    Stain colour deconvolution results for a colon tissue image. by Najah Alsubaie (3633154)

    Published 2017
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  7. 147
    Results of nuclei detection algorithm in [2, 28] trained and tested for different stain deconvolution algorithms.

    Results of nuclei detection algorithm in [2, 28] trained and tested for different stain deconvolution algorithms. by Najah Alsubaie (3633154)

    Published 2017
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  8. 148
    Correlation between the density maps and the ground truth with the associated <i>p-values</i> above each method for the H (left) and E (right) stains in all the three datasets.

    Correlation between the density maps and the ground truth with the associated <i>p-values</i> above each method for the H (left) and E (right) stains in all the three datasets. by Najah Alsubaie (3633154)

    Published 2017
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  9. 149
    Bland Altman plot for the proposed method (left) and ICA [12] (right) for H and E stains using all datasets.

    Bland Altman plot for the proposed method (left) and ICA [12] (right) for H and E stains using all datasets. by Najah Alsubaie (3633154)

    Published 2017
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  10. 150
    Euclidean Distance between the estimated stain matrix and the ground truth.

    Euclidean Distance between the estimated stain matrix and the ground truth. by Najah Alsubaie (3633154)

    Published 2017
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  11. 151
    Correlation between the density maps and the ground truth.

    Correlation between the density maps and the ground truth. by Najah Alsubaie (3633154)

    Published 2017
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  12. 152
    Data and code.

    Data and code. by Najah Alsubaie (3633154)

    Published 2017
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  13. 153
    Blind source separation using sub-band decomposition with ICA.

    Blind source separation using sub-band decomposition with ICA. by Najah Alsubaie (3633154)

    Published 2017
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  14. 154
    Block diagram of the proposed method.

    Block diagram of the proposed method. by Najah Alsubaie (3633154)

    Published 2017
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  15. 155
    Sample images from the datasets used in our experiments.

    Sample images from the datasets used in our experiments. by Najah Alsubaie (3633154)

    Published 2017
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  16. 156
    Estimation of Eosin channel for a sample image.

    Estimation of Eosin channel for a sample image. by Najah Alsubaie (3633154)

    Published 2017
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  17. 157
    Rapid Protein Global Fold Determination Using Ultrasparse Sampling, High-Dynamic Range Artifact Suppression, and Time-Shared NOESY

    Rapid Protein Global Fold Determination Using Ultrasparse Sampling, High-Dynamic Range Artifact Suppression, and Time-Shared NOESY by Brian E. Coggins (2023777)

    Published 2016
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  18. 158
    Rapid Protein Global Fold Determination Using Ultrasparse Sampling, High-Dynamic Range Artifact Suppression, and Time-Shared NOESY

    Rapid Protein Global Fold Determination Using Ultrasparse Sampling, High-Dynamic Range Artifact Suppression, and Time-Shared NOESY by Brian E. Coggins (2023777)

    Published 2016
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  19. 159
    A 440 Hz tuning fork captured at 2329 fps using only ambient lighting.

    A 440 Hz tuning fork captured at 2329 fps using only ambient lighting. by Yamn Chalich (8816588)

    Published 2020
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  20. 160
    FoM comparison of several low-cost, high-speed cameras against our prototype.

    FoM comparison of several low-cost, high-speed cameras against our prototype. by Yamn Chalich (8816588)

    Published 2020
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