Research The Power of Multimodal Learning (in 5 Charts) When students engage multiple senses to learn—drawing or acting out a concept, for example—they’re more likely to remember and develop a deeper ...

Learning from multimodal sources offers the unprecedented possibility of capturing correspondences between modalities and gaining in-depth insights in a variety of domains.

We included studies that reported deep learning techniques such as convolutional neural networks (CNNs), transformers, or neural networks in their methods. The aim of this study was to identify the ...

Learning from multimodal sources offers the unprecedented possibility of capturing correspondences between modalities and gaining in-depth insights in a variety of domains.

This repository contains the code and data for the paper "Multimodal Learning for Traffic Risk Prediction: Combining Aerial Imagery with Contextual Data." This study introduces a novel deep learning ...

Multimodal machine learning tasks have gained significant popularity and demonstrated promising results in mul-timodal data analysis. However, existing multimodal approaches primarily focus on ...

We propose Multimodal fine-grained interaction with the Multiple Contrastive Learning (M CL) model for image-text multi-modal sentiment detection. Specifically, we first obtain the reinforced global ...

Learning with all your senses: Multimodal enrichment as the optimal learning strategy of the future Date: February 1, 2023 Source: Technische Universität Dresden Summary: Neuroscientists have ...