There are 1 repository under shufflenet topic.
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)
YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931) ECCV Workshops 2022)
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
常用的语义分割架构结构综述以及代码复现 华为媒体研究院 图文Caption、OCR识别、图视文多模态理解与生成相关方向工作或实习欢迎咨询 15757172165 https://guanfuchen.github.io/media/hw_zhaopin_20220724_tiny.jpg
More readable and flexible yolov5 with more backbone(gcn, resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer, etc) and (cbam,dcn and so on), and tensorrt
Light-weight Single Person Pose Estimator
Model Compression—YOLOv3 with multi lightweight backbones(ShuffleNetV2 HuaWei GhostNet), attention, prune and quantization
This is a fast caffe implementation of ShuffleNet.
ShuffleNet Implementation in TensorFlow
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.
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。
PyTorch implementation for 3D CNN models for medical image data (1 channel gray scale images).
⛵️ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]
Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project
Official implementation of "RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection".
VoVNet, MobileNet, ShuffleNet, HarDNet, GhostNet, EfficientNet backbone networks and SKU-110K dataset for detectron2
Official implementation of "CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer".
This code includes classification and detection tasks in Computer Vision, and semantic segmentation task will be added later.
A collection of deep learning models (PyTorch implemtation)
DenseShuffleNet for Semantic Segmentation using Caffe for Cityscapes and Mapillary Vistas Dataset
Implementation of MobileNet, MobileNetv2, ShuffleNet, ShuffleNetv2, EfficientNet in Pytorch.
Implementation of ShuffleNet V2 architecture
Shufflenet implementation in tensorflow based on https://arxiv.org/abs/1707.01083
Implemented the training and inference of several common deep learning model algorithms with tensorflow and pytorch.
Architectures of convolutional neural networks for image classification in PyTorch
Image Classification Training Framework for Network Distillation
Implemented multiple face detection algorithms to accurately count and save recognized faces in a designated folder, enhancing detection accuracy. Integrated ShuffleNet and MTCNN successfully. Developed intelligent graphics for project analysis in Excel. Implemented facial recognition using PCA and Eigenfaces for dataset matching.
Implemented multiple face detection algorithms to accurately count and save recognized faces in a designated folder, enhancing detection accuracy. Integrated ShuffleNet and MTCNN successfully. Developed intelligent graphics for project analysis in Excel. Implemented facial recognition using PCA and Eigenfaces for dataset matching.