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Showing 1 - 20 results of 8,556 for search '(((( based imaging algorithm ) OR ( data learning algorithm ))) OR ( element method algorithm ))', query time: 0.39s Refine Results
  1. 1
    Performance of machine learning algorithms.

    Performance of machine learning algorithms. by Wenxue Liu (6877754)

    Published 2025
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  2. 2
    Performance of different machine learning algorithms.

    Performance of different machine learning algorithms. by Apichat Suratanee (634281)

    Published 2024
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  3. 3
    The performance matrix of different machine learning algorithms.

    The performance matrix of different machine learning algorithms. by Ahmad M. Al-Omari (20460931)

    Published 2024
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  4. 4
    Machine learning prediction algorithm flow chart.

    Machine learning prediction algorithm flow chart. by Ahmad M. Al-Omari (20460931)

    Published 2024
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  5. 5
    Algorithm deployment.

    Algorithm deployment. by Bo Tong (2138632)

    Published 2025
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  6. 6
    ML algorithms in cyber security.

    ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

    Published 2025
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  7. 7
    Facial Expression Image Dataset for Computer Vision Algorithms

    Facial Expression Image Dataset for Computer Vision Algorithms by Ali Alameer (12549592)

    Published 2025
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  8. 8
    Supplementary file 1_The value of unsupervised machine learning algorithms based on CT and MRI for predicting sarcopenia.doc

    Supplementary file 1_The value of unsupervised machine learning algorithms based on CT and MRI for predicting sarcopenia.doc by Huayan Zuo (22308277)

    Published 2025
    “…Objectives<p>This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold partitioning, in predicting sarcopenia based on computed tomography (CT) and magnetic resonance imaging (MRI) data.…”
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  9. 9
    Data_Sheet_1_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.CSV

    Data_Sheet_1_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.CSV by Jie Shen (31533)

    Published 2024
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  10. 10
    Data_Sheet_2_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.docx

    Data_Sheet_2_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.docx by Jie Shen (31533)

    Published 2024
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  11. 11
    Supporting data for "Using AI-based Deep Learning Algorithms for Nowcasting Cloud Evolution"

    Supporting data for "Using AI-based Deep Learning Algorithms for Nowcasting Cloud Evolution" by Xianqi Jiang (9391832)

    Published 2025
    “…To this end, this study, ''Using AI-based Deep Learning Algorithms for Nowcasting Cloud Evolution'', focuses on using AI-based deep learning algorithms for accurate nowcasting of cloud evolution. …”
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  12. 12
    Algorithmic experimental parameter design.

    Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

    Published 2024
    “…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
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  13. 13
    Optimal hyperparameters of the model-agnostic meta-learning algorithm with few-shot tasks.

    Optimal hyperparameters of the model-agnostic meta-learning algorithm with few-shot tasks. by Soraya Khanmohmmadi (21539953)

    Published 2025
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  14. 14
    Spatial spectrum estimation for three algorithms.

    Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

    Published 2024
    “…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
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  15. 15
    Explained variance ration of the PCA algorithm.

    Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

    Published 2025
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  16. 16
    IOU values of four algorithms.

    IOU values of four algorithms. by Hong Li (20183)

    Published 2024
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  17. 17
    Comparison of results based on CycleGAN method.

    Comparison of results based on CycleGAN method. by Xiaojun Wang (50332)

    Published 2025
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  18. 18
    Comparison of tracing algorithms on FF image (region of interest). Image was applied to algorithms with three different filters: Original/no filtering, Gaussian and DnCnn. Data corresponds to images traced; GT is the manually delineated ground truth. For the evaluation of Tracing Algorithms, the GT fibres are represented in red, algorithm tracing is depicted in blue and areas where they overlap is white.

    Comparison of tracing algorithms on FF image (region of interest). Image was applied to algorithms with three different filters: Original/no filtering, Gaussian and DnCnn. Data cor... by Youssef Arafat (21009293)

    Published 2025
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  19. 19
    Comparison of tracing algorithms on DME image (full view) [42]. Image was applied to algorithms with three different filters: Original/no filtering, Gaussian and DnCnn. Data corresponds to images traced; GT is the manually delineated ground truth. For the evaluation of Tracing Algorithms, the GT fibres are represented in red, algorithm tracing is depicted in blue and areas where they overlap is white.

    Comparison of tracing algorithms on DME image (full view) [42]. Image was applied to algorithms with three different filters: Original/no filtering, Gaussian and DnCnn. Data corres... by Youssef Arafat (21009293)

    Published 2025
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  20. 20
    Comparison of tracing algorithms on SHG image (full view) [40]. Image was applied to algorithms with three different filters: Original/no filtering, Gaussian and DnCnn. Data corresponds to the tracing images; GT is the manually delineated ground truth. For the evaluation of Tracing Algorithms, the GT fibres are represented in red, algorithm tracing is depicted in blue and areas where they overlap is white.

    Comparison of tracing algorithms on SHG image (full view) [40]. Image was applied to algorithms with three different filters: Original/no filtering, Gaussian and DnCnn. Data corres... by Youssef Arafat (21009293)

    Published 2025
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