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cifar10-5class-5k

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img
imagewidth (px)
32
32
label
class label
5 classes
0airplane
4deer
1automobile
2bird
1automobile
1automobile
1automobile
1automobile
2bird
1automobile
1automobile
0airplane
4deer
4deer
0airplane
3cat
1automobile
4deer
3cat
4deer
4deer
2bird
2bird
2bird
3cat
4deer
0airplane
1automobile
3cat
3cat
4deer
4deer
2bird
0airplane
3cat
2bird
3cat
0airplane
2bird
0airplane
0airplane
2bird
0airplane
2bird
0airplane
4deer
2bird
3cat
1automobile
4deer
4deer
3cat
0airplane
1automobile
3cat
2bird
4deer
3cat
2bird
3cat
1automobile
0airplane
0airplane
1automobile
3cat
1automobile
1automobile
3cat
2bird
1automobile
1automobile
0airplane
4deer
1automobile
0airplane
0airplane
1automobile
1automobile
0airplane
0airplane
3cat
4deer
3cat
2bird
3cat
2bird
0airplane
1automobile
2bird
3cat
1automobile
2bird
1automobile
3cat
3cat
0airplane
1automobile
2bird
3cat
3cat
End of preview. Expand in Data Studio

Please see uoft-cs/cifar10 for the original dataset. This is a downsampled version for CSC-413.

To cite:

@TECHREPORT{Krizhevsky09learningmultiple,
    author = {Alex Krizhevsky},
    title = {Learning multiple layers of features from tiny images},
    institution = {},
    year = {2009}
}
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Collection including r-three/cifar10-5class-5k