Tag: multimodal fusion

Researchers in Beijing developed an expert-guided large language model that extracts interpretable speech-based biomarkers of psychological resilience in major depressive ...

Researchers have developed AttentiveGaze, a real-time multimodal AI framework that fuses face, eye, and head pose cues with attention mechanisms ...

A new deep learning model called TimePop shows that the exact time a short video is posted carries a powerful ...

Researchers at Lanzhou University have developed AMGFM, a multimodal AI model that fuses EEG, eye movement, and pupil signals to ...

Researchers have developed RL-Axial, a segmentation framework that uses reinforcement learning to decide for each image patch whether to apply ...

A new study systematically tests early, late, and hybrid fusion strategies for combining image and text in AI systems that ...

Chinese researchers have developed CGFM, an attention-guided fusion module that lets YOLOv8-based detectors intelligently combine visible-light and infrared satellite imagery, ...

Researchers have introduced a Riemannian manifold-based loss function that pushes multimodal Transformer models to state-of-the-art accuracy in human activity recognition ...

Researchers in China have developed a Multimodal Transformer Attention model that jointly extracts and fuses video, audio and text features ...

A new neural network called CDGaitFusion fuses shared motion patterns with individual-specific features to recognize people by their gait despite ...