CIFAR-10 Dataset Introduction
编辑日期: 2024-07-20 文章阅读: 次
The CIFAR-10 dataset is a widely-used benchmark dataset in the field of machine learning and computer vision. It consists of 60,000 color images in 10 classes, with 6,000 images per class. The dataset is divided into 50,000 training images and 10,000 test images. Each image is 32x32 pixels in size.
The CIFAR-10 dataset contains the following 10 classes (labels):
- Airplane: Images of various types of airplanes.
- Automobile: Images of different kinds of vehicles, such as cars and trucks.
- Bird: Images of birds, including different species and postures.
- Cat: Images of domestic cats in various poses and environments.
- Deer: Images of deer, including various species and backgrounds.
- Dog: Images of domestic dogs of different breeds and postures.
- Frog: Images of frogs, showing various species and natural settings.
- Horse: Images of horses, including different breeds and activities.
- Ship: Images of ships, including boats and other watercraft.
- Truck: Images of trucks, including different types and sizes.
Each class has 6,000 images, and the dataset is designed to be challenging due to the variability in object appearance, position, and background. The CIFAR-10 dataset is commonly used for training machine learning models to classify images into these 10 categories.
