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Invertebrates, ranging from arthropods to mollusks, exhibit an astonishing diversity of sensory modalities and behaviors. These organisms navigate complex ...

Abstract: Remote sensed mapping data and seafloor in-situ imagery are often gathered to infer benthic habitat distributions. However, leveraging multimodal data is challenging because of inherent ...

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

Blended Learning mixes traditional teaching with technology to personalize the learning experience for each student. “Our ...

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 ...