Search alternatives:
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
based optimization » whale optimization (Expand Search)
primary case » primary cause (Expand Search), primary care (Expand Search), primary causes (Expand Search)
image driven » climate driven (Expand Search), wave driven (Expand Search), mapk driven (Expand Search)
case based » made based (Expand Search), game based (Expand Search), rate based (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
based optimization » whale optimization (Expand Search)
primary case » primary cause (Expand Search), primary care (Expand Search), primary causes (Expand Search)
image driven » climate driven (Expand Search), wave driven (Expand Search), mapk driven (Expand Search)
case based » made based (Expand Search), game based (Expand Search), rate based (Expand Search)
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41
Loss vs. Epoch.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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42
Sample images from the BreakHis dataset.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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43
Accuracy vs. Epoch.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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44
Segmentation results of the proposed model.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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45
S1 Dataset -
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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46
CSCO’s flowchart.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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52
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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53
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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54
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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55
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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56
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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57
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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58
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. …”
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59
Bi-directional 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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60