Probability of detection analysis of SST-CRN model under fading channels. حسب Saraswathi M. (19353597)

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Pd analysis of the SST-CRN model under fading channels. حسب Saraswathi M. (19353597)

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Probability of error analysis of SST-CRN under fading channels. حسب Saraswathi M. (19353597)

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Pmd analysis of the SST-CRN model. حسب Saraswathi M. (19353597)

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Pd analysis of the SST-CRN model under non-fading channels. حسب Saraswathi M. (19353597)

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Structure of DBN model. حسب Saraswathi M. (19353597)

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Probability of error analysis of SST-CRN model under non-fading channels. حسب Saraswathi M. (19353597)

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GA process. حسب Jianpeng Zhang (528185)

"…GA is used to optimize the feature selection process to identify the key feature subsets that have the greatest impact on model performance. …"

IRBMO vs. variant comparison adaptation data. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Performance comparison of our proposed model with existing approaches for cattle weight prediction using machine learning and deep learning techniques. حسب Md Junayed Hossain (22615268)

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Visualization of Residuals across different models applied in our research. حسب Md Junayed Hossain (22615268)

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Proposed architecture of our research. حسب Md Junayed Hossain (22615268)

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Validation Loss vs. Training Loss Curves for the CNN architectures and EfficientNet B3 model evaluated in this study. حسب Md Junayed Hossain (22615268)

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A summary of the dataset containing information on each cattle’s weight, breed, and height. حسب Md Junayed Hossain (22615268)

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Error case analysis using LIME visualization on cattle’s weight prediction. حسب Md Junayed Hossain (22615268)

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Height-Weight correlation and breed distribution of cattle in the dataset. حسب Md Junayed Hossain (22615268)

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Comparison of Actual vs. Predicted values across different models used in this study. حسب Md Junayed Hossain (22615268)

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This figure illustrates the four distinct custom Convolutional Neural Network (CNN) architectures evaluated in this study. حسب Md Junayed Hossain (22615268)

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Here are the samples prediction of cattle weight using our proposed best 3Conv3Dense model. حسب Md Junayed Hossain (22615268)

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Data collision free processing unit. حسب Ayesha Waris (21368446)