Characteristics of CIFAR10 Dataset
The common characterstics of CIFAR10 dataset include:
- Number of Instances: 60,000 images
- Training Set:
- 50,000 images
- Each image is a 32×32 color image (RGB), resulting in a shape of (32, 32, 3).
- Images are divided into 10 classes, with 5,000 images per class.
- Test Set:
- 10,000 images
- Same structure as the training set, with 1,000 images per class.
- Pixel Values: Each pixel value (0-255) represents the grayscale intensity of the corresponding pixel in the image.
- Target: Target Column represents the type of clothing item (0-9)
- Number of Attributes: 1 (32×32 pixels = 1024 pixels)
CIFAR10 DataSet in Keras (Tensorflow) for Object Recognition
The CIFAR-10 dataset is readily accessible in Python through the Keras library, which is part of TensorFlow, making it a convenient choice for developers and researchers working on machine learning projects, especially in image classification. In this article, we will explore CIFAR10 (classification of 10 image labels) from Keras/tensorflow.
Table of Content
- What is the CIFAR10 Keras/Tensorflow Datasets?
- Characteristics of CIFAR10 Dataset
- How to Load CIFAR10 (classification of 10 image labels) keras Datasets?
- Significance of CIFAR10 in Machine Learning
- Applications of the CIFAR10 Dataset:
- FAQ – CIFAR10 – Keras/Tensorflow Datasets
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