Statements (76)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Database_Management_System
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:Transformers_character
gptkb:CIFAR-10 gptkb:Dense_Net gptkb:Res_Net |
| gptkbp:contains |
100 classes
600 images per class coarse labels fine labels |
| gptkbp:data_type |
benchmarking algorithms
|
| gptkbp:developed_by |
gptkb:Alex_Krizhevsky
|
| gptkbp:has |
10,000 test images
32,000 training images |
| https://www.w3.org/2000/01/rdf-schema#label |
CIFAR-100
|
| gptkbp:is_a_resource_for |
computer vision education
|
| gptkbp:is_analyzed_in |
model performance
model robustness overfitting issues class imbalance issues transfer learning effectiveness |
| gptkbp:is_available_on |
https://www.cs.toronto.edu/~kriz/cifar.html
|
| gptkbp:is_compared_to |
gptkb:Image_Net
other datasets |
| gptkbp:is_divided_into |
training and test sets
|
| gptkbp:is_evaluated_by |
accuracy
cross-validation |
| gptkbp:is_implemented_in |
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch |
| gptkbp:is_known_for |
small image size
|
| gptkbp:is_often_used_in |
machine learning research
|
| gptkbp:is_part_of |
computer vision datasets
open-source datasets |
| gptkbp:is_popular_in |
computer vision practitioners
|
| gptkbp:is_referenced_in |
academic papers
|
| gptkbp:is_similar_to |
gptkb:CIFAR-10
|
| gptkbp:is_tested_for |
image classification algorithms
|
| gptkbp:is_used_for |
image classification
data augmentation techniques deep learning benchmarks |
| gptkbp:is_used_in |
data visualization techniques
educational purposes convolutional neural networks data preprocessing techniques visual recognition tasks computer vision competitions real-world applications. adversarial training research data labeling projects image retrieval studies model interpretability research real-time image processing studies style transfer studies transfer learning studies |
| gptkbp:is_utilized_in |
gptkb:physicist
feature extraction studies |
| gptkbp:performance |
image recognition tasks
image segmentation tasks image generation models |
| gptkbp:provides_information_on |
object detection tasks
supervised learning tasks anomaly detection tasks feature learning tasks image captioning tasks image clustering tasks image enhancement tasks image quality assessment tasks image synthesis tasks multi-class classification tasks semi-supervised learning tasks unsupervised learning tasks |
| gptkbp:released_in |
gptkb:2010
|
| gptkbp:resolution |
32x32 pixels
|
| gptkbp:scientific_classification |
20 superclasses
|
| gptkbp:set_in |
CIFAR
|
| gptkbp:training |
deep learning models
|