Popular GitHub Repositories for Dnn

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

Open standard for machine learning interoperability

Experience, Learn and Code the latest breakthrough innovations with Microsoft AI

Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2

NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego

Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving (ICCV, 2019)

仅使用numpy从头开始实现神经网络,包括反向传播公式推导过程; numpy构建全连接层、卷积层、池化层、Flatten层；以及图像分类案例及精调网络案例等,持续更新中... ...

Tutorial for computer vision and machine learning in PHP 7/8 by opencv (installation + examples + documentation)

HLS based Deep Neural Network Accelerator Library for Xilinx Ultrascale+ MPSoCs

Optimized (for size and speed) Caffe lib for iOS and Android with out-of-the-box demo APP.

Heterogeneous Run Time version of Caffe. Added heterogeneous capabilities to the Caffe, 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 Caffe architecture which users deploy their applications seamlessly.

ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python)

LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks

Repository collecting papers about neuromorphic hardware, such as ASIC and FPGA implementations of SNNs and stuff.

An Open Source Deep Learning Inference Engine Based on FPGA

Lowest barrier of entry to Image Processing, Computer Vision and Neural Networks on the JavaVM

这是AI游戏助手的最新版代码库，其他的代码库已停止更新。AI游戏助手截取游戏屏幕进行对象识别，模拟自动瞄准/自动开枪等功能，提升玩家的游戏体验。这个版本使用onnx+yoyov6进行AI推理，微软的onnx在个人电脑上运行效率很高，配合美团的yoyov6对象检测模型，游戏图像检测速度快到飞起。

Demo of implement YOLO v3 with OpenCvSharp v4 on C#