CIFAR 10 & CIFAR 100
CIFAR-10 and CIFAR-100 are labeled image datasets for computer vision and machine learning, with 60,000 32x32 color images in 10 or 100 classes.
Score
30
User Rating
3.0
Free/Trial Support
Not Supported
Starting Price
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Last Updated
Aug 04, 2026
Overview
What is CIFAR 10 & CIFAR 100?
CIFAR-10 and CIFAR-100 are benchmark datasets created by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton, consisting of 60,000 32x32 color images divided into training and test sets for image classification tasks.
What is CIFAR 10 & CIFAR 100 used for?
Top Features
- 60,000 32x32 color images
- 10 or 100 classes
- Training and test splits
- Multiple format versions (Python, Matlab, binary)
- Baseline results provided
How to use CIFAR 10 & CIFAR 100?
Download the dataset in Python, Matlab, or binary format, load it using provided scripts, and use it for training and evaluating machine learning models, such as convolutional neural networks, with baseline results available for reference.
Alternative Tools
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Pros & Cons
Pros
- Widely used benchmark
- Free to download and use
- Well-documented layout
- Suitable for beginners and researchers
Cons
- Small image size (32x32)
- Limited to specific classes
- No built-in tools for augmentation
Use Cases
- Machine learning research
- Computer vision education
- Model benchmarking
- Algorithm development
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