There are 1 repository under shufflenet topic.
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
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)
OpenMMLab Image Classification Toolbox and Benchmark
YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931)
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)
常用的语义分割架构结构综述以及代码复现
Light-weight Single Person Pose Estimator
This is a fast caffe implementation of ShuffleNet.
Model Compression—YOLOv3 with multi lightweight backbones(ShuffleNetV2 HuaWei GhostNet), attention, prune and quantization
ShuffleNet Implementation in TensorFlow
More readable and flexible yolov5 with more backbone(resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer) and (cbam,dcn and so on), and tensorrt
Single Path One-Shot NAS MXNet implementation with full training and searching pipeline. Support both Block and Channel Selection. Searched models better than the original paper are provided.
⛵️ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]
💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.
Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project
VoVNet, MobileNet, ShuffleNet, HarDNet, GhostNet, EfficientNet backbone networks and SKU-110K dataset for detectron2
A collection of deep learning models (PyTorch implemtation)
用于pytorch的图像分类,包含多种模型方法,比如AlexNet,VGG,GoogleNet,ResNet,DenseNet等等,包含可完整运行的代码。除此之外,也有colab的在线运行代码,可以直接在colab在线运行查看结果。也可以迁移到自己的数据集进行迁移学习。
DenseShuffleNet for Semantic Segmentation using Caffe for Cityscapes and Mapillary Vistas Dataset
PyTorch implementation for 3D CNN models for medical image data (1 channel gray scale images).
Implementation of MobileNet, MobileNetv2, ShuffleNet, ShuffleNetv2, EfficientNet in Pytorch.
Implementation of ShuffleNet V2 architecture
Multi image label classification by multi models.
Shufflenet implementation in tensorflow based on https://arxiv.org/abs/1707.01083
Architectures of convolutional neural networks for image classification in PyTorch
Single Shot MultiBox Detector in TensorFlow,Please pay attention to my branch about shufflenet-tensorflow.
Facebook AI Performance Evaluation Platform