Search alternatives:
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
primary deep » primary sleep (Expand Search), primary level (Expand Search), primary dates (Expand Search)
binary msc » binary mask (Expand Search)
msc driven » msc derived (Expand Search), us driven (Expand Search)
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
primary deep » primary sleep (Expand Search), primary level (Expand Search), primary dates (Expand Search)
binary msc » binary mask (Expand Search)
msc driven » msc derived (Expand Search), us driven (Expand Search)
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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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Models’ performance without optimization.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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RNN performance comparison with/out optimization.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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Proposed reinforcement learning architecture.
Published 2025“…Experimental evaluation were conducted employing Deep Q Networks (DQN) and Proximal Policy Optimization (PPO) algorithms within ViZDoom and Unity reinforcement learning environments. …”
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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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Proposed method approach.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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LSTM model performance.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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Descriptive statistics.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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CNN-LSTM Model performance.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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MLP Model performance.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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RNN Model performance.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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CNN Model performance.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”