MNIST Large Scale dataset
Introduced by Jansson et al. in Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges
The MNIST Large Scale dataset is based on the classic MNIST dataset, but contains large scale variations up to a factor of 16. The motivation behind creating this dataset was to enable testing the ability of different algorithms to learn in the presence of large scale variability and specifically the ability to generalise to new scales not present in the training set over wide scale ranges.
The dataset contains training data for each one of the relative size factors 1, 2 and 4 relative to the original MNIST dataset and testing data for relative scaling factors between 1/2 and 8, with a ratio of $\sqrt[4]{2}$ between adjacent scales.
Benchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
|
MNIST Large Scale dataset
|
FovAvg Single-scale training
|
Papers
| Paper | Code | Results | Date | Stars |
|---|
