Search alternatives:
largest decrease » larger decrease (Expand Search)
marked decrease » marked increase (Expand Search)
cnn decrease » nn decrease (Expand Search), mean decrease (Expand Search), _ decrease (Expand Search)
largest decrease » larger decrease (Expand Search)
marked decrease » marked increase (Expand Search)
cnn decrease » nn decrease (Expand Search), mean decrease (Expand Search), _ decrease (Expand Search)
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CNN Model Architecture.
Published 2025“…The research introduces a new method called SMOTE-based Convolutional Neural Network (CNN) technology to detect areas impacted by Invasive Ductal Carcinoma (IDC) in whole slide pictures. …”
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CNN framework.
Published 2025“…We propose to implement both MLP (Multilayer Perceptron) and CNN (Convolutional Neural Networks) based on conventional methods to detect the Denial of Services (DDoS) attack. …”
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CNN frameworks.
Published 2025“…We propose to implement both MLP (Multilayer Perceptron) and CNN (Convolutional Neural Networks) based on conventional methods to detect the Denial of Services (DDoS) attack. …”
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Flowchart of Proposed SMO_CNN.
Published 2025“…The research introduces a new method called SMOTE-based Convolutional Neural Network (CNN) technology to detect areas impacted by Invasive Ductal Carcinoma (IDC) in whole slide pictures. …”
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CNN Model Layers Summary.
Published 2025“…The research introduces a new method called SMOTE-based Convolutional Neural Network (CNN) technology to detect areas impacted by Invasive Ductal Carcinoma (IDC) in whole slide pictures. …”
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Performance Results of Proposed SMO_CNN Model.
Published 2025“…The research introduces a new method called SMOTE-based Convolutional Neural Network (CNN) technology to detect areas impacted by Invasive Ductal Carcinoma (IDC) in whole slide pictures. …”
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Repetitive stress induces a decrease in sound-evoked activity.
Published 2025“…<p>(a) Left: noise-evoked activity rates at different noise intensities for chronically tracked PPys cells in baseline and repeated stress conditions (<i>N</i> = 5 mice, <i>n</i> = 285 neurons, mean ± SE). …”
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