New AI Architecture Sharpens Breast Tumor Detection Across Four Imaging Modalities
Researchers have developed a Swin Transformer-based U-Net with a novel SECA cross-attention decoder that improves breast tumor segmentation accuracy across ...
Researchers have developed a Swin Transformer-based U-Net with a novel SECA cross-attention decoder that improves breast tumor segmentation accuracy across ...
A new multimodal AI framework called TriCCA-PPI fuses sequence, structure, and functional data through chained cross-attention to predict protein-protein interactions ...
Researchers have developed CALT-GNN, a graph neural network that combines cross-attention-based multi-omics integration with long-tail expert routing to improve cancer ...
A controlled ablation study shows that classifier design and optimisation, not cross-attention alone, account for most of the improvement a ...
Researchers at Shenzhen Technology University report a LiDAR segmentation framework that reaches 74.4 percent mean IoU on SemanticKITTI and 83.5 ...
A multimodal AI model called ERF-BA-TFD+ detects and localizes audio-visual deepfakes by cross-reconstructing audio and video features and reasoning over ...
A new hierarchical cross-attention framework integrates mRNA, microRNA, and DNA methylation data to classify breast cancer subtypes more accurately and ...
A new data-fusion study over Taiwan shows that gridded ionospheric TEC provides modest complementary information for retrospective earthquake maximum-magnitude estimation, ...
Researchers have unveiled SyncDIT, a diffusion-transformer framework that generates high-fidelity video synchronized frame-by-frame to complex audio such as musical performances, ...
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© 2025 Scienmag - Science Magazine