Tag: multimodal fusion

A deep learning framework pairing cross-attention memory networks with dhole optimization predicts audience immersion in digital twin art environments with ...

A digital twin framework combining visual saliency and multimodal fusion accurately predicted physical smart home user interactions and improved operational ...

A new machine learning framework combining multimodal sensor fusion and contrastive learning improves induction motor fault classification accuracy to 84.31%.

Researchers have introduced a physics-guided graph transformer framework that combines convolutional features, transformer attention, and graph topology for automated multimodal ...

A multicenter study demonstrates that integrating clinical, radiomics, habitat, and deep learning MRI features improves preoperative prediction of axillary lymph ...

Researchers have developed IoT ArtNet, an intelligent framework combining deep learning and Internet of Things gesture sensing to dynamically drive ...

A review of 42 studies finds speech emotion systems degrade by an average of 8.6 percent and facial systems by ...

Researchers have introduced VCE-GM, a generative model guided by visual communication elements that improves consistency, error rates, and aesthetic quality ...

An explainable transformer model fusing MRI with texture descriptors reached over 99 percent accuracy in Alzheimer's disease staging benchmarks, with ...

GAMPoint, a geometry-augmented transformer built on Point Transformer V3, delivers modest, category-dependent gains in 3D indoor point-cloud segmentation on S3DIS ...