MNIST

E74103

benchmark dataset dataset handwritten digit dataset

MNIST is a widely used benchmark dataset of handwritten digit images commonly employed for training and evaluating image classification algorithms in machine learning and computer vision.

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All labels observed (5)

Label	Occurrences
MNIST canonical	13
MNIST database	3
MNIST dataset	3
MNIST handwritten digit database	1
Yann LeCun's MNIST website	1

Statements (47)

Predicate	Object
instanceOf	benchmark dataset ⓘ dataset ⓘ handwritten digit dataset ⓘ
backgroundColor	black ⓘ
basedOn	NIST Special Database 1 ⓘ NIST Special Database 3 ⓘ
benchmarkStatus	canonical toy dataset in machine learning ⓘ
classLabels	digits 0 through 9 ⓘ
commonModelType	convolutional neural network ⓘ multilayer perceptron ⓘ
creator	Christopher J. C. Burges ⓘ Corinna Cortes ⓘ Yann LeCun ⓘ
dataSource	scanned handwritten digits ⓘ
dataType	grayscale images ⓘ
digitColor	white ⓘ
domain	computer vision ⓘ machine learning ⓘ
fileFormat	IDX ⓘ
fullName	Modified National Institute of Standards and Technology database ⓘ
hostedBy	Yann LeCun’s website ⓘ
imageChannels	1 ⓘ
imageFile	t10k-images-idx3-ubyte ⓘ train-images-idx3-ubyte ⓘ
imageHeight	28 pixels ⓘ
imageResolution	28x28 pixels ⓘ
imageWidth	28 pixels ⓘ
inspiredDataset	EMNIST ⓘ Fashion-MNIST ⓘ KMNIST ⓘ
introducedInPublication	Gradient-based learning applied to document recognition ⓘ
labelFile	t10k-labels-idx1-ubyte ⓘ train-labels-idx1-ubyte ⓘ
license	freely available for research and educational use ⓘ
numberOfClasses	10 ⓘ
preprocessingStep	centering in a fixed-size image ⓘ size normalization ⓘ
publicationYear	1998 ⓘ
task	handwritten digit recognition ⓘ image classification ⓘ
testSetSize	10000 ⓘ
totalImages	70000 ⓘ
trainingSetSize	60000 ⓘ
typicalUse	benchmarking classification algorithms ⓘ educational examples in deep learning ⓘ training neural networks ⓘ
valueRange	0 to 255 grayscale intensity ⓘ

Referenced by (21)

Full triples — surface form annotated when it differs from this entity's canonical label.

LeNet → notableDataset → MNIST ⓘ

“A fast learning algorithm for deep belief nets” → evaluationDataset → MNIST ⓘ

subject surface form: A fast learning algorithm for deep belief nets

Gradient-based learning applied to document recognition → datasetUsed → MNIST ⓘ

torchvision (ecosystem) → dataset → MNIST ⓘ

subject surface form: torchvision

PixelRNN → datasetUsed → MNIST ⓘ

Modified National Institute of Standards and Technology database → abbreviation → MNIST ⓘ

Corinna Cortes → knownFor → MNIST ⓘ

this entity surface form: MNIST dataset

Corinna Cortes → coDeveloperOf → MNIST ⓘ

this entity surface form: MNIST dataset

Corinna Cortes → notableWork → MNIST ⓘ

this entity surface form: MNIST handwritten digit database

NIST Special Database 1 → influenced → MNIST ⓘ

this entity surface form: MNIST database

NIST Special Database 1 → sourceFor → MNIST ⓘ

this entity surface form: MNIST database

IDX → usedIn → MNIST ⓘ

this entity surface form: MNIST dataset

IDX → commonlyDistributedBy → MNIST ⓘ

this entity surface form: Yann LeCun's MNIST website

Fashion-MNIST → similarTo → MNIST ⓘ

Fashion-MNIST → moreChallengingThan → MNIST ⓘ

KMNIST → comparedTo → MNIST ⓘ

KMNIST → inspiredBy → MNIST ⓘ

EMNIST → basedOn → MNIST ⓘ

EMNIST → extends → MNIST ⓘ

EMNIST → relatedTo → MNIST ⓘ

NIST Special Database 3 → influenced → MNIST ⓘ

this entity surface form: MNIST database