weiaicunzai/pytorch-cifar100
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)
This project offers a collection of pre-configured deep learning models for image classification. It takes image datasets (like CIFAR-100) as input and outputs trained image recognition models, along with performance metrics. Machine learning engineers and researchers can use this to quickly experiment with different neural network architectures.
4,755 stars. No commits in the last 6 months.
Use this if you need to quickly train and evaluate various state-of-the-art image classification models on the CIFAR-100 dataset.
Not ideal if you're looking for a user-friendly application to classify images without deep learning expertise, or if you need advanced training tricks beyond basic optimization.
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Jul 15, 2024
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