In industries, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and safety. However, conventional methods rely on heavy computational processing and image enhancement and may not truly reflect subtle defects, particularly in low-light settings. Now, researchers have designed a robust model with noise suppression and illumination-adaptive features that enhance the accuracy and consistency of anomaly detection across diverse surfaces and textures in poorly lit industrial environments.

The Heinz College of Information Systems and Public Policy will work with the National University of Singapore (NUS) Yong Loo Lin School of Medicine (NUS Medicine) and School of Computing (NUS Computing), and with the firm FriendsLearn, to promote joint research and development activities of mutual interest. The research will use artificial intelligence (AI) in precision prevention of disease via innovative digital therapeutic solutions such as digital vaccines.

More than 100 experts in molecular simulation, coordinated by IRB Barcelona, have published an article in Nature Methods advocating for a paradigm shift in molecular dynamics data management. The article defends the implementation of the FAIR principles (Findable, Accessible, Interoperable, Reusable) to improve the reproducibility of calculations and facilitate their later use as a source of information on the flexibility of biomacromolecules. Led by Drs. Modesto Orozco and Adam Hospital, the article proposes the establishment of a shared infrastructure for storing and reusing data in the context of the AI revolution.