Currently, deep learning is the most important technique for solving many complex machine vision problems. State-of-the-art deep learning models typically contain a very large number of parameters ...

Georgia Tech researchers Vidya Muthukumar and Eva Dyer are leading a multi-institutional project to develop a theory for data augmentation, aiming to improve the generalization and fairness of AI ...

Widespread interest in artificial intelligence (AI) in health care has focused mainly on deductive systems that analyze available real-world data to discover patterns not otherwise visible. Generative ...

The task of point cloud classification suffers from the problem of insufficient data, and data augmentation is an effective method to alleviate this problem. However, the effect of conventional ...

A conditional generative adversarial network architecture was implemented to generate synthetic data. Use cases were myelodysplastic syndromes (MDS) and AML: 7,133 patients were included. A fully ...

Forbes contributors publish independent expert analyses and insights. I write about how to drive more value with data and analytics. While many are looking at AI automating data storytelling, it's ...

A new technical paper titled “An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design” was published by researchers at the University of Texas at Austin, Nvidia ...

Ambuj Tewari receives funding from NSF and NIH. You’ve just finished a strenuous hike to the top of a mountain. You’re exhausted but elated. The view of the city below is gorgeous, and you want to ...