Popular GitHub Repositories for Squeezenet

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)

High level network definitions with pre-trained weights in TensorFlow

AoE (AI on Edge，终端智能，边缘计算) 是一个终端侧AI集成运行时环境 (IRE)，帮助开发者提升效率。

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

The squeezenet image classification android example

[EXPERIMENTAL] Demo of using PyTorch 1.0 inside an Android app. Test with your own deep neural network such as ResNet18/SqueezeNet/MobileNet v2 and a phone camera.

An improved version of SqueezeNet networks https://github.com/DeepScale/SqueezeNet

TensorFlow version of SqueezeNet with converted pretrained weights

Find out how to describe the things around you in another language with Core ML and the Vision framework in iOS 11! ?

Image classification using Transfer learning technique. Updated and added mlflow with PyTorch fine-tune tutorial

A project developed and maintained as part of the aim at bringing current capabilities in machine learning and artificial intelligence into practical use for non-programmers and average computer users.

A performance benchmark of recent image classification models in deep learning

Attention Squeeze U-Net

Real time camera object detection with Machine Learning in swift. Basic introduction to Core ML, Vision and ARKit.

Traffic sign classifier and CoreML implementation.

VGG | Resnet | Alexnet | Squeezenet | Densenet | Inception

官方所有Models实现

An app that uses CoreML and SqueezeNet to take a picture and tell what the object it thinks is in the picture!

Snap List is an iOS app, which utilizes CoreML and SqueezeNet model to detect items using the user's camera and allows the user to add them to their list with persistence using UserDefaults.