Search alternatives:
process optimization » model optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
phase process » phase proteins (Expand Search), whole process (Expand Search), phase protein (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based codon » based color (Expand Search), based cohort (Expand Search), based action (Expand Search)
process optimization » model optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
phase process » phase proteins (Expand Search), whole process (Expand Search), phase protein (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based codon » based color (Expand Search), based cohort (Expand Search), based action (Expand Search)
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Flow chart of particle swarm algorithm.
Published 2024“…The third phase is the training and testing phase. Finally, the best-performing model was selected and compared with the currently established models (Alexnet, Squeezenet, Googlenet, Resnet50).…”
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Proposed architecture testing phase.
Published 2025“…The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. The trained model is employed in the testing phase for the feature extraction from the self-attention layer and passed to the shallow wide neural network classifier for the final classification. …”
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The structure of the Resnet50.
Published 2024“…The third phase is the training and testing phase. Finally, the best-performing model was selected and compared with the currently established models (Alexnet, Squeezenet, Googlenet, Resnet50).…”
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The bottleneck residual block for Resnet50.
Published 2024“…The third phase is the training and testing phase. Finally, the best-performing model was selected and compared with the currently established models (Alexnet, Squeezenet, Googlenet, Resnet50).…”
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DeepDate model’s architecture design.
Published 2024“…The third phase is the training and testing phase. Finally, the best-performing model was selected and compared with the currently established models (Alexnet, Squeezenet, Googlenet, Resnet50).…”
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Comparison with existing SOTA techniques.
Published 2025“…The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. The trained model is employed in the testing phase for the feature extraction from the self-attention layer and passed to the shallow wide neural network classifier for the final classification. …”