Dataset Groups Activity Stream Learning Multiple Layers of Features from Tiny Images The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image. BibTex: @dataset{Alex_Krizhevsky_2024, abstract = {The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.}, author = {Alex Krizhevsky}, doi = {10.57702/zp44cu3g}, institution = {No Organization}, keyword = {'AlexNet', 'CIFAR', 'CIFAR-10', 'CIFAR-100', 'Computer Vision', 'Deep Learning', 'Image Classification', 'Image Recognition', 'Tiny Images', 'color images', 'convolutional neural networks', 'image classification', 'tiny images'}, month = {dec}, publisher = {TIB}, title = {Learning Multiple Layers of Features from Tiny Images}, url = {https://service.tib.eu/ldmservice/dataset/learning-multiple-layers-of-features-from-tiny-images}, year = {2024} }