Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

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)

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

Caffe models (including classification, detection and segmentation) and deploy files for famouse networks

Classification with PyTorch.

Classification models trained on ImageNet. Keras.

Simple Tensorflow implementation of "Squeeze and Excitation Networks" using Cifar10 (ResNeXt, Inception-v4, Inception-resnet-v2)

A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).

PyTorch implementation of CNNs for CIFAR benchmark

Reproduces ResNet-V3 with pytorch

CBAM implementation on TensowFlow

Speech commands recognition with PyTorch | Kaggle 10th place solution in TensorFlow Speech Recognition Challenge

PyTorch implementation for 3D CNN models for medical image data (1 channel gray scale images).

SE_ResNet && SE_ResNeXt with pretrained weights on ImageNet (SENet In TensorFlow)

基于tf.keras的多标签多分类模型

Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project

PyTorch-style and human-readable RegNet with a spectrum of pre-trained models

COVID-Next -> Pytorch upgrade of the COVID-Net for COVID-19 detection in X-Ray images

PyTorch implementation of Dynamic Grouping Convolution and Groupable ConvNet with pre-trained G-ResNeXt models

Implement and Compare VGG, ResNet and ResNeXt on CIFAR-10