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 ...

However, traditional clinical trial designs are often ill-suited for rare disease research with common challenges including ...

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 ...

Synthetic data generation (SDG) was proposed in the early nineties as a form of imputation. 1 Since then, multiple statistical and machine learning (ML) methods have been developed to generate ...

The lower the uncertainty in solar resource data, the lower the investment costs. IEA PVPS Task 16 has organized and published two benchmarks to make uncertainty of models and data comparable – a ...

The researchers have developed a new approach to making biometric presentation attack detection (PAD) resistant to demographic bias.