https://github.com/narpat78/image-classification-using-cnn
https://github.com/narpat78/image-classification-using-cnn
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/narpat78/image-classification-using-cnn
- Owner: narpat78
- Created: 2025-03-12T15:58:42.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-03-19T05:04:42.000Z (3 months ago)
- Last Synced: 2025-03-19T06:21:52.458Z (3 months ago)
- Language: Jupyter Notebook
- Size: 606 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# **Image-Classification-using-CNN**
## **CIFAR-10 Dataset**
The **CIFAR-10** (Canadian Institute for Advanced Research) dataset is a widely used benchmark dataset in computer vision and deep learning. It consists of **60,000 color images** categorized into **10 classes**, with **6,000 images per class**. The dataset is divided into:
- **50,000 training images**
- **10,000 test images**
Each image is **32×32** pixels with **3 color channels (RGB)**. The dataset is often used for training and evaluating image classification models.
**Classes in CIFAR-10**
The dataset includes the following 10 object categories:
Image Source: Papers With Code