MIT researchers say they have found a more efficient way to train machine learning models that predict how complex metal alloys will behave.

Abstract: Medical datasets are usually imbalanced, where negative cases severely outnumber positive cases. Therefore, it is essential to deal with this data skew problem when training machine learning ...

A toolkit for actively pairing conditions in pairwise comparison preference aggregation. Pairwise comparison data arise in many domains with subjective assessment experiments. In these experiments ...

UTokyo and Kubota develop a drone potato yield prediction method combining multispectral imagery, AI, and growth models.

Abstract: Coordinate measuring machines are widely used in the precision measurement of manufacturing workpieces. However, the nature of a point-by-point probing characteristic limits their efficiency ...

MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal ...

Objectives Elective non-emergent surgical wait times have increased across countries such as Canada, straining operating room ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

Zhu, Weiqiang, and Gregory C. Beroza. "PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method." arXiv preprint arXiv:1803.03211 (2018). Liu, Min, et al. "Rapid characterization of ...

DAAAM enhances autonomous systems' spatiotemporal capabilities by integrating real-time 4D scene graphs with rich language ...