Artificial neural networks (ANN) are computational systems that “learn” to perform tasks by considering examples, generally without being programmed with any task-specific rules.
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
simple neural network library in ANSI C
High-efficiency floating-point neural network inference operators for mobile, server, and Web
Acceleration package for neural networks on multi-core CPUs
A lightweight C library for artificial neural networks
Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving (ICCV, 2019)
A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.
🤖 A portable, header-only, artificial neural network library written in C99
Ruby library for interfacing with FANN (Fast Artificial Neural Network)
Open Neural Network Exchange to C compiler.
🌓 Bringing pjreddie's DarkNet out of the shadows #yolo
Light version of convolutional neural network Yolo v3 & v2 for objects detection with a minimum of dependencies (INT8-inference, BIT1-XNOR-inference)
Next Generation Flight Controller Firmware
💥 Fast matrix-multiplication as a self-contained Python library – no system dependencies!
Real time monaural source separation base on fully convolutional neural network operates on Time-frequency domain.
N2D2 is an open source CAD framework for Deep Neural Network simulation and full DNN-based applications building.
A neural network to smartly create coherent terminal colorschemes based on an image.
INSTA - Instant Volumetric Head Avatars [Demo]
The style transfer android example