Along with the dataset, Encord has created a new methodology for training multimodal AI models. It’s called EBind, and the ...

Multi-modal infrastructure boosts economic growth, increases property values, and supports tourism while improving community ...

Managing children’s screen time has evolved from strict limits to mindful guidance. Experts emphasise quality, context, and ...

"I didn’t expect her to continue with this, but she’s done quite a bit of work." Teen prodigy turns heads with cutting-edge ...

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...

With optical/imaging sensors holding a commanding 35.0% market share, and key regions like Asia Pacific, North America, and ...

This interesting study adapts machine learning tools to analyze movements of a chromatin locus in living cells in response to serum starvation. The machine learning approach developed is useful, the ...

Abstract: Multimodal deep learning integrates diverse data types to enhance model performance by capturing complex interactions between different modalities. Traditional models Fare limited to single ...

Although artificial intelligence has already shown promise in cardiovascular medicine, most existing tools analyze only one type of data—such as electrocardiograms or cardiac images—limiting their ...