Self-attention improves EEG workload classification in one multitasking study
A four-head self-attention module raised cross-validated EEG workload classification accuracy from 80.73% to 91.33% during SIMKAP multitasking in one study, ...
A four-head self-attention module raised cross-validated EEG workload classification accuracy from 80.73% to 91.33% during SIMKAP multitasking in one study, ...
A stacking ensemble combining EfficientNet, ResNet and MobileNet classified healthy and diseased olive leaf images with 97.21% accuracy on a ...
A hybrid DeiT system reached 99.13% accuracy on a 38-class plant disease benchmark while combining local and global AI explanations ...
A comparative study of sugar beet and maize seedling imagery found that a custom CNN outperformed classical classifiers, while U-Net ...
A hybrid model combining bidirectional deep learning, attention and fuzzy reasoning reported 98.8% accuracy on a 2,500-observation macro-financial policy dataset ...
A conditional diffusion model reached an F1-score of 0.975 when detecting abnormal data in a 90-day, 18-channel bridge monitoring dataset ...
A review of 34 studies finds that artificial intelligence performs well at analyzing mycorrhizal root images, but limited external and ...
A controlled study of 40 smart home app users found that multimodal behavioral analysis guided prototype redesigns associated with lower ...
A CNN that fuses shallow and deep lesion features classified rice blast severity with about 93% accuracy and estimated the ...
A controlled study reports that MCGE-Net enhanced images using reference images, text and pixel labels, outperforming comparison methods across medical, ...
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© 2026 Scienmag - Science Magazine