EMBL-EBI scientists and collaborators at Heidelberg University have developed CORNETO, a new computational tool that uses machine learning to gain meaningful insights from complex biological data.

A new data-driven technique for obstacle avoidance in autonomous vehicles is reported in the International Journal of Vehicle ...

A new high-resolution flood dataset, FloodPlanet, is enhancing satellite-based flood monitoring through more accurate training of deep learning ...

While some business leaders buy large language models, others build their own. Here are five things you need to know.

Achieving high efficiency, long operational lifetime, and excellent color purity is essential for organic light-emitting ...

Model for predicting molecular crystal properties is readily adaptable to specific tasks, even with limited data ...

Zero-knowledge proofs add a crucial integrity layer to AI moderation, enabling companies to verify decisions without exposing ...

ChatGPT-style models are being trained to detect what a news article really thinks about an issue – even when that stance is ...

Forecasting electricity demand in buildings is now more accurate with Group Encoding (GE), a new method that uses only ...

This study presents a non-invasive approach to detect anxiety and depression through gait analysis and machine learning, utilizing Microsoft Kinect technology.

Accurately predicting the remaining useful life (RUL) of lithium-ion batteries is crucial for the safety and reliability of electric vehicles (EVs). Although data-driven approaches have been ...

Fiber-optic ATR-IR spectroscopy enables real-time liver tumor classification during surgery, offering faster and more objective diagnostics with machine learning support.