Abstract
A key aspect to developing and successfully deploying neural network (NN)-based solutions is the availability of suitable datasets. In this article some of the challenges to acquire and annotate data are discussed in the context of new consumer devices. To increase the sample size of training data several approaches to augment a seed dataset are explained and discussed including a number of advanced, problem-specific techniques. A basic introduction to the concept of learned data augmentation is also provided.
| Original language | English |
|---|---|
| Pages | 48-54 |
| Number of pages | 7 |
| Volume | 9 |
| No. | 3 |
| Specialist publication | IEEE Consumer Electronics Magazine |
| DOIs | |
| Publication status | Published - May 2020 |