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Showing 1 - 20 results of 20 for search '(( binary _ codon optimization algorithm ) OR ( binary image pre detection algorithm ))', query time: 0.57s Refine Results
  1. 1
    Comparison of images before and after pre-processing: the original image (left) and after applying top-hat and bottom-hat filters (right).

    Comparison of images before and after pre-processing: the original image (left) and after applying top-hat and bottom-hat filters (right). by Rinrada Tanthanathewin (18611171)

    Published 2024
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  2. 2
    Automatic Pre-Processing (APP).

    Automatic Pre-Processing (APP). by Yuxiang Wu (748543)

    Published 2022
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  3. 3
    Lung cancer CT images before and after pre-processing.

    Lung cancer CT images before and after pre-processing. by Md. Sabbir Hossain (9958939)

    Published 2025
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  4. 4
    Hair removal preprocessing using the DullRazor algorithm before image generation.

    Hair removal preprocessing using the DullRazor algorithm before image generation. by Mujung Kim (22367223)

    Published 2025
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  5. 5
    Image_1_Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.pdf

    Image_1_Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.pdf by Konrad Stawiski (4753380)

    Published 2024
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  6. 6
    Pre-processing of raw images for pose estimation using physical model-trained convolutional neural network model.

    Pre-processing of raw images for pose estimation using physical model-trained convolutional neural network model. by Aniket Ravan (3174171)

    Published 2023
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  7. 7
    Image3_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg

    Image3_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

    Published 2024
    “…The platform combines CIELAB and YCbCr color space segmentation with a pre-trained YOLOv5s algorithm for wound localization. …”
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  8. 8
    Image4_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg

    Image4_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

    Published 2024
    “…The platform combines CIELAB and YCbCr color space segmentation with a pre-trained YOLOv5s algorithm for wound localization. …”
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  9. 9
    Image1_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg

    Image1_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

    Published 2024
    “…The platform combines CIELAB and YCbCr color space segmentation with a pre-trained YOLOv5s algorithm for wound localization. …”
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  10. 10
    Image2_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg

    Image2_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

    Published 2024
    “…The platform combines CIELAB and YCbCr color space segmentation with a pre-trained YOLOv5s algorithm for wound localization. …”
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  11. 11
    Image5_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg

    Image5_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

    Published 2024
    “…The platform combines CIELAB and YCbCr color space segmentation with a pre-trained YOLOv5s algorithm for wound localization. …”
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  12. 12
    Segmentation, trace denoising and spike extraction framework.

    Segmentation, trace denoising and spike extraction framework. by Changjia Cai (10647521)

    Published 2021
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  13. 13
    Table_1_Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.docx

    Table_1_Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.docx by Hyo-jae Lee (11780051)

    Published 2021
    “…Objective<p>This study was conducted in order to investigate the feasibility of using radiomics analysis (RA) with machine learning algorithms based on breast magnetic resonance (MR) images for discriminating malignant from benign MR-detected additional lesions in patients with primary breast cancer.…”
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  14. 14
    Table_1_Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.docx

    Table_1_Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.docx by Hyo-jae Lee (11780051)

    Published 2021
    “…Objective<p>This study was conducted in order to investigate the feasibility of using radiomics analysis (RA) with machine learning algorithms based on breast magnetic resonance (MR) images for discriminating malignant from benign MR-detected additional lesions in patients with primary breast cancer.…”
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  15. 15
    Flowchart of software workflow.

    Flowchart of software workflow. by Gavrielle R. Untracht (11820311)

    Published 2021
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  16. 16
    PathOlOgics_RBCs Python Scripts.zip

    PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

    Published 2023
    “…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”
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  17. 17
    Table1_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.docx

    Table1_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.docx by Varun Sendilraj (19732510)

    Published 2024
    “…The platform combines CIELAB and YCbCr color space segmentation with a pre-trained YOLOv5s algorithm for wound localization. …”
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  18. 18
    Image_3_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.pdf

    Image_3_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.pdf by Ting Li (117885)

    Published 2020
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  19. 19
    Image_2_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.tif

    Image_2_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.tif by Ting Li (117885)

    Published 2020
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  20. 20
    Image_1_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.tif

    Image_1_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.tif by Ting Li (117885)

    Published 2020
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