swarajkumarsingh/cnn-cifar-classification-model

Cifar classification model using Pytorch CNN module with ResNet9 model, with CUDA for training to archive 75% accuracy

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Experimental

This project offers a pre-built Convolutional Neural Network (CNN) designed for classifying small color images into one of ten common categories like 'airplane', 'dog', or 'truck'. You provide the image, and it outputs the predicted category. This is useful for researchers or students learning about image classification and neural networks, or for those who need a baseline model for classifying similar small-scale image data.

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Use this if you need to classify small color images (like 32x32 pixels) into 10 distinct categories and want to understand or apply a standard CNN approach.

Not ideal if you need to classify images larger than 32x32 pixels, require a custom set of categories, or need very high accuracy for critical applications beyond an introductory benchmark.

image-classification computer-vision deep-learning-education pattern-recognition machine-learning-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 0 / 25

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Jupyter Notebook

License

MIT

Last pushed

Sep 18, 2024

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