Statements (64)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Database_Management_System
|
| gptkbp:bfsLayer |
6
|
| gptkbp:bfsParent |
gptkb:Matching_networks
|
| gptkbp:application |
machine learning research
|
| gptkbp:class |
gptkb:Person
gptkb:fish gptkb:mythological_figure gptkb:seal insects flowers small mammals trees reptiles large carnivores beaver aquatic mammals food containers medium-sized mammals fruit and vegetables household electrical devices household furniture large man-made outdoor things vehicles 1 vehicles 10 vehicles 11 vehicles 12 vehicles 13 vehicles 14 vehicles 15 vehicles 16 vehicles 17 vehicles 18 vehicles 19 vehicles 2 vehicles 20 vehicles 3 vehicles 4 vehicles 5 vehicles 6 vehicles 7 vehicles 8 vehicles 9 |
| gptkbp:contains |
100 classes
600 images per class |
| gptkbp:created_by |
gptkb:Alex_Krizhevsky
|
| gptkbp:data_type |
color images
|
| gptkbp:distribution |
uniform across classes
|
| gptkbp:format |
RGB
binary |
| gptkbp:has_content |
https://www.cs.toronto.edu/~kriz/cifar.html
|
| gptkbp:has_website |
computer vision
|
| gptkbp:historical_source |
gptkb:Canadian_Institute_for_Advanced_Research
|
| https://www.w3.org/2000/01/rdf-schema#label |
CIFAR-100 dataset
|
| gptkbp:image |
60000
|
| gptkbp:is_divided_into |
10,000 test images
50,000 training images |
| gptkbp:is_documented_in |
supervised
|
| gptkbp:is_evaluated_by |
accuracy
|
| gptkbp:is_similar_to |
gptkb:CIFAR-10_dataset
|
| gptkbp:is_used_for |
image classification
|
| gptkbp:label |
fine and coarse labels
|
| gptkbp:release_year |
gptkb:2010
|
| gptkbp:requires |
gptkb:theorem
|
| gptkbp:resolution |
32x32 pixels
|