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WideResNets for CIFAR10/100 implemented in PyTorch. This implementation requires less GPU memory than what is required by the official Torch implementation: ...
Best CIFAR-10, CIFAR-100 results with wide-residual networks using PyTorch - bmsookim/wide-resnet ... git clone https://github.com/meliketoy/wide-resnet.pytorch ...
Wide-Resnet-28-10 Tensorflow implementation. The code achieves about 95.56% accuracy in 120 epochs on CIFAR10 dataset, which is similar to the original PyTorch ...
The Places365-CNNs for Scene Classification . Contribute to CSAILVision/places365 development by creating an account on GitHub.
We call the resulting network structures wide residual networks (WRNs) and show that these are far superior over their commonly used thin and very deep ...
2016/5/23 -WideResNet50 is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more ...
Wide Residual networks simply have increased number of channels compared to ResNet. Otherwise the architecture is the same. Deeper ImageNet models with ...
2021/7/8 -Pretrained wideresnet and xception71 · Issue #149 · NVIDIA/semantic-segmentation ... Pretrained wideresnet and xception71 #149. New issue.
A new adversarial purification method that uses the forward and reverse processes of diffusion models to remove adversarial perturbations.
3.8% and 18.3% on CIFAR-10 and CIFAR-100. Contribute to szagoruyko/wide-residual-networks development by creating an account on GitHub.