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Showing 1 - 6 results of 6 for search '(( binary image robust classification algorithm ) OR ( binary based gpu optimization algorithm ))', query time: 0.48s Refine Results
  1. 1
    Objective performance of fully-automated SLAVV software.

    Objective performance of fully-automated SLAVV software. by Samuel A. Mihelic (11539996)

    Published 2021
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  2. 2
    DataSheet_1_Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT Imaging.pdf

    DataSheet_1_Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT I... by Mengshi Dong (5181833)

    Published 2021
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  3. 3
    Result comparison with other existing models.

    Result comparison with other existing models. by Md. Sabbir Hossain (9958939)

    Published 2025
    “…The main objective of this research is to harness the noble strategies of artificial intelligence for identifying and classifying lung cancers more precisely from CT scan images at the early stage. This study introduces a novel lung cancer detection method, which was mainly focused on Convolutional Neural Networks (CNN) and was later customized for binary and multiclass classification utilizing a publicly available dataset of chest CT scan images of lung cancer. …”
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  4. 4
    Dataset distribution.

    Dataset distribution. by Md. Sabbir Hossain (9958939)

    Published 2025
    “…The main objective of this research is to harness the noble strategies of artificial intelligence for identifying and classifying lung cancers more precisely from CT scan images at the early stage. This study introduces a novel lung cancer detection method, which was mainly focused on Convolutional Neural Networks (CNN) and was later customized for binary and multiclass classification utilizing a publicly available dataset of chest CT scan images of lung cancer. …”
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  5. 5
    CNN structure for feature extraction.

    CNN structure for feature extraction. by Md. Sabbir Hossain (9958939)

    Published 2025
    “…The main objective of this research is to harness the noble strategies of artificial intelligence for identifying and classifying lung cancers more precisely from CT scan images at the early stage. This study introduces a novel lung cancer detection method, which was mainly focused on Convolutional Neural Networks (CNN) and was later customized for binary and multiclass classification utilizing a publicly available dataset of chest CT scan images of lung cancer. …”
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  6. 6
    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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