CIFAR-10 and CIFAR-100 datasets
cs.toronto.edu · 1,266 words · saved by 1 readers
< Back to Alex Krizhevsky's home page
CIFAR-10 and CIFAR-100 datasets The CIFAR-10 and CIFAR-100 datasets are labeled subsets of the 80 million tiny images dataset. CIFAR-10 and CIFAR-100 were created by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The CIFAR-10 dataset The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the
related reading
- Convolutional Neural Network (CNN) | TensorFlow Coretensorflow.org
- Dataset list - A list of the biggest machine learning datasetsdatasetlist.com
- SELECT: A Large-Scale Benchmark of Data Curation Strategies for Image Classificationarxiv.org
- ImageNet Classification with Deep Convolutional Neural Networksproceedings.neurips.cc
- CodaLab Worksheetsworksheets.codalab.org
- Why you need to improve your training data, and how to do it << Pete Warden's blogpetewarden.com
- GitHub - awesomedata/awesome-public-datasets: A topic-centric list of HQ open datasets. · GitHubgithub.com
- Datasets – Hugging Facehuggingface.co
- lecture_2.pdfcs231n.stanford.edu
- Index of /exdb/mnistyann.lecun.com
- Teachable Machineteachablemachine.withgoogle.com
- SynthRAD2025 Grand Challenge dataset: Trainingzenodo.org