Search alternatives:
phase optimization » whale optimization (Expand Search), based optimization (Expand Search), path optimization (Expand Search)
binary marked » binary mask (Expand Search)
binary change » binary image (Expand Search)
marked phase » market case (Expand Search), marked scale (Expand Search), marker base (Expand Search)
change phase » change rate (Expand Search), change based (Expand Search), change poses (Expand Search)
phase optimization » whale optimization (Expand Search), based optimization (Expand Search), path optimization (Expand Search)
binary marked » binary mask (Expand Search)
binary change » binary image (Expand Search)
marked phase » market case (Expand Search), marked scale (Expand Search), marker base (Expand Search)
change phase » change rate (Expand Search), change based (Expand Search), change poses (Expand Search)
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GSE96058 information.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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The performance of classifiers.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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3
Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx
Published 2025“…The results showed significant stage-based changes in the maturity states of litchi fruits: during the rapid growth phase, the fruit count increased by 18.28%; during the maturity differentiation phase, semi-mature fruits accounted for approximately 53%; and during the peak maturity phase, mature fruits exceeded 50%, with a fruit drop rate of 11.46%. …”
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Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
Published 2022“…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”