#计算机科学#Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, N...
翻译 - 在cifar100上进行实践（ResNet，DenseNet，VGG，GoogleNet，InceptionV3，InceptionV4，Inception-ResNetv2，Xception，Resnet In Resnet，ResNext，ShuffleNet，ShuffleNetv2，MobileNet，MobileNetv2，SqueezeNet，NasNet，残留注意力网络，SENet）
Attention Branch Network (CIFAR100, ImageNet models)
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST
High-acc(>0.7) model(ResNet, ResNeXt, DenseNet, SENet, SE-ResNeXt) on TensorFlow.
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
This is the PyTorch-0.4.0 implementation of few-shot learning on CIFAR-100 with graph neural networks (GNN)
2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552
3.41% and 17.11% error on CIFAR-10 and CIFAR-100
Build PyTorch CIFAR100 using coarse labels
ResNet50 pretrained transfer learning for CIFAR100 in Pytorch
Pytorch implements the VGG19 model to classify cifar100
Cifar100 in alexnet network model under the highest accuracy
CIFAR10, CIFAR100 results with VGG16,Resnet50,WideResnet using pytorch-lightning
An unofficial implementation of 《Deep Mutual Learning》 by Pytorch to do classification on cifar100.
Simple object classification project with deep-learning. We choose CIFAR10, CIFAR100 and Caltech101 as training datasets.
SimpleAICV:pytorch training and testing examples.
Implementation of Vision Transformer from scratch and performance compared to standard CNNs (ResNets) and pre-trained ViT on CIFAR10 and CIFAR100.