Search alternatives:
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
based optimization » whale optimization (Expand Search)
primary data » primary care (Expand Search)
image driven » climate driven (Expand Search), wave driven (Expand Search), mapk driven (Expand Search)
data based » data used (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
based optimization » whale optimization (Expand Search)
primary data » primary care (Expand Search)
image driven » climate driven (Expand Search), wave driven (Expand Search), mapk driven (Expand Search)
data based » data used (Expand Search)
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Comparative analysis of DDcGAN-GSOM’s Energy Consumption, Throughput, and Dealy.
Published 2025Subjects: -
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Performance metrics for BrC.
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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Proposed CVAE 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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Proposed methodology.
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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Loss vs. Epoch.
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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Sample images from the BreakHis dataset.
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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Accuracy vs. Epoch.
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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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. …”