Tag: cross-modal attention

Researchers in South Korea have developed a multimodal deep learning model that fuses visual analysis and textual rubrics to automatically ...

Researchers have developed GRaFiT, an image-text classification framework that dynamically reroutes fusion at the token, branch, and view levels to ...

Researchers at Hefei University have developed AMCF, a multimodal AI model that combines bidirectional text-image attention with dual-branch gated fusion ...

Researchers have developed RViTCANet, a multimodal deep learning framework that recognizes drones from millimeter wave radar cross section data with ...

A new multi-task AI framework fuses raw waveforms, spectral features, and statistics through bidirectional cross-modal attention to detect heart murmurs, ...