Search alternatives:
segmentation algorithm » selection algorithm (Expand Search)
process segmentation » process recommendation (Expand Search), cell segmentation (Expand Search), process simulation (Expand Search)
models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
primary data » primary care (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary risk » primary risk (Expand Search), dietary risk (Expand Search)
risk models » risk model (Expand Search)
segmentation algorithm » selection algorithm (Expand Search)
process segmentation » process recommendation (Expand Search), cell segmentation (Expand Search), process simulation (Expand Search)
models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
primary data » primary care (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary risk » primary risk (Expand Search), dietary risk (Expand Search)
risk models » risk model (Expand Search)
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Segmentation results of the proposed model.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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Features selected by optimization algorithms.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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Hybrid feature selection algorithm of CSCO-ROA.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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