ncnn is a high-performance neural network inference framework optimized for the mobile platform

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

nGraph has moved to OpenVINO

(New version is out: https://github.com/hpi-xnor/BMXNet-v2) BMXNet: An Open-Source Binary Neural Network Implementation Based on MXNet

C++ project to implement MTCNN, a perfect face detect algorithm, on different DL frameworks. The most popular frameworks: caffe/mxnet/tensorflow, are all suppported now

BMXNet 2: An Open-Source Binary Neural Network Implementation Based on MXNet

Support Yolov5(4.0)/Yolov5(5.0)/YoloR/YoloX/Yolov4/Yolov3/CenterNet/CenterFace/RetinaFace/Classify/Unet. use darknet/libtorch/pytorch/mxnet to onnx to tensorrt

This is an implematation project of face detection and recognition. The face detection using MTCNN algorithm, and recognition using LightenenCNN algorithm.

Tengine Convert Tool supports converting multi framworks' models into tmfile that suitable for Tengine-Lite AI framework.

A lightweight parameter server interface

Heterogeneous Run Time version of MXNet. Added heterogeneous capabilities to the MXNet, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original MXNet architecture which users deploy their applications seamlessly.

[this repo is no longer maintained] Neural Network image classifier (inception-bn network architecture), developed via MxNet

crnn in mxnet.can train with chinese characters

A pipeline for 3D face recognition(FR), including data preprocessing, feature extraction and face recognition. Suit for consumer RGB-D cameras, for example, Kinect V2.

Train Neuronal networks to automate your home

ShuffleNetV1 &ShuffleNetV2 implementation in mxnet

Mxnet2Caffe_Tensor RT

the loss function in Aritcal ‘Focal Loss for Dense Object Detection‘’

A mxnet implement of the paper "Beyond a Gaussian Denoiser : Residual Learning of Deep CNN for Image Denoising" for VapourSynth