Neural networks

A novel machine learning model predicts wear and tear in manufacturing parts with less real-world data for cost savings and improved productivity.

A new method to create artificial synapses developed by A*STAR researchers could make neural networks more efficient and less energy-intensive.

A*STAR researchers have created the first machine learning model for predicting clinical outcomes of stem cell therapies in patients with cartilage disorders.

Artificial neural networks are now being used to make 3D-printed metal structures more accurately—and stronger—than ever before.

A machine learning technique developed by A*STAR scientists could help patients with locked-in syndrome communicate via brain-machine interfaces.

A*STAR scientists have designed sophisticated machine learning techniques that are more efficient at identifying anomalies in datasets.

Using deep-learning techniques to locate potential human activities in videos

Neural networks that function like the human visual cortex may help realize faster, more reliable pattern recognition