Machine learning

A hybrid approach combining deep learning with Bayesian inference has enabled more accurate, efficient and automatic crack detection.

By breaking complex actions into their basic components, researchers have developed a versatile framework that enables robots to learn from human demonstrators.

Leveraging both artificial intelligence and field knowledge may prove to be a superior strategy for predicting machine health.

A large genetic study has identified distinct features of lung cancer in East Asians, which which could improve prediction and treatment outcomes.

Researchers have created a new computational framework that is set to transform the online shopping experience.

A new deep learning method increases the accuracy and range of applications for computer vision platforms.

A new machine learning technique can predict the dynamics between microbes and therapeutics with unprecedented accuracy.

A*STAR researchers use digital drug simulators to predict the efficacies of repurposed antivirals for treating COVID-19.

Researchers are simulating real-world complexity in machine learning models to ensure their safety before they are deployed in the wild.

A*STAR scientists can now classify immune cell populations with greater precision thanks to a machine-learning algorithm.

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.