|
gptkbp:instance_of
|
gptkb:Data
|
|
gptkbp:application
|
object detection
|
|
gptkbp:available_at
|
https://www.cs.toronto.edu/~kriz/cifar.html
|
|
gptkbp:class_count
|
gptkb:10
|
|
gptkbp:contains
|
60,000 images
10,000 test images
50,000 training images
|
|
gptkbp:created_by
|
gptkb:Alex_Krizhevsky
|
|
gptkbp:data_license
|
non-commercial use only
|
|
gptkbp:data_preprocessing
|
normalization
|
|
gptkbp:data_type
|
binary
supervised
compressed
color images
multiclass classification
|
|
gptkbp:evaluates
|
accuracy
cross-validation
requires test data
|
|
gptkbp:evaluation_type
|
classification accuracy
|
|
gptkbp:field_of_study
|
gptkb:Artificial_Intelligence
|
|
gptkbp:format
|
PNG
|
|
gptkbp:has_artwork
|
60,000
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
CIFAR-10
|
|
gptkbp:image_format
|
RGB
|
|
gptkbp:influenced
|
gptkb:Image_Net
gptkb:MNIST
|
|
gptkbp:is_divided_into
|
training and testing
10 classes
|
|
gptkbp:is_popular_in
|
deep learning community
|
|
gptkbp:model_training
|
requires labeled data
|
|
gptkbp:performance
|
image classification
|
|
gptkbp:predecessor
|
gptkb:CIFAR-100
|
|
gptkbp:provides_information_on
|
gptkb:University_of_Toronto
open access
rotation and flipping
|
|
gptkbp:release_year
|
gptkb:2009
|
|
gptkbp:research_areas
|
computer vision
|
|
gptkbp:research_challenge
|
overfitting
class imbalance
data augmentation
underfitting
|
|
gptkbp:research_focus
|
image recognition
|
|
gptkbp:resolution
|
32x32 pixels
|
|
gptkbp:scientific_classification
|
gptkb:deer
gptkb:bird
gptkb:ship
gptkb:horse_race
gptkb:aircraft
gptkb:Cat
gptkb:vehicles
gptkb:Dog
gptkb:automobile
gptkb:Toad
|
|
gptkbp:storage
|
local or cloud
|
|
gptkbp:successor
|
gptkb:None
|
|
gptkbp:test_set_size
|
10,000 images
|
|
gptkbp:training_set_size
|
50,000 images
|
|
gptkbp:used_by
|
gptkb:students
gptkb:developers
gptkb:researchers
|
|
gptkbp:used_in
|
machine learning research
computer vision tasks
|
|
gptkbp:bfsParent
|
gptkb:machine_learning
|
|
gptkbp:bfsLayer
|
3
|