Machine learning

Applying a machine learning algorithm to the analysis of immunology datasets, A*STAR scientists can now classify immune cell populations with greater precision.

A*STAR scientists have developed a generative adversarial network that can accurately classify clothing images and realistically manipulate specific image attributes.

A*STAR scientists have devised a learning framework to enable machines to integrate visual, auditory and text data.

Researchers across A*STAR are developing the hardware and software needed to take factories to the next level in Industry 4.0.

Machine learning could pave the way for the creation of novel alloys for a range of practical applications, say scientists at A*STAR.

Researchers at A*STAR have designed a hybrid machine learning model to enhance touch capabilities in robots.

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

A*STAR researchers have devised a machine learning strategy that can be applied to translation and other complex classification problems.

A*STAR researchers have developed a deep learning method to more accurately measure sleep duration and quality.

An automated machine learning system for analyzing leg movements in fruit flies is helping A*STAR researchers shed light on how neurodegenerative diseases develop.

A new model called DECAPROP is helping machines to read more efficiently by enhancing their ability to understand the context of words.

A*STAR researchers have devised a machine learning technique to help antivirus developers stay ahead in the cat-and-mouse game of Android malware detection.