High-efficiency floating-point neural network inference operators for mobile, server, and Web
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Updated
Jul 16, 2024 - C
High-efficiency floating-point neural network inference operators for mobile, server, and Web
ConvLIB is a library of convolution kernels for multicore processors with ARM (NEON) or RISC-V architecture
Convolutional Interactive Artificial Neural Networks by/for Astrophysicists
A system for creating neural networks in C
A small and modular Neural Networks library for C programs
A series of machine learning trigger bots for Counter-Strike: Global Offensive (CS:GO).
A machine learning trigger bot for Quake3 Arena & Quake Live.
A C implementation of common Artificial Neural Networks
A framework for the creation and training of vanilla and convolutional neural nets only depending on a C compiler and standard library
An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)
Identify the emotion of multiple speakers in an Audio Segment
Rede convolucional em C. Camadas Conv, ConvNc, Pool, PoolAv, Relu, Softmax, BatchNorm, DropOut, FullConnect.
This repository contains the implementation of a real-time human gender detection application using an optimized Darknet Library. For accurate detection of faces closer or farther from the camera, YOLOv3 architecture is used. It was trained on a modified FDDB dataset
neural network for C programmers
Machine learning methods and image processing were utilized to determine whether a surface contains a deformity. Through the development of a C++ program to generate surface deformities given image length, width, maximum deformity radius, and sample size as the training set, we utilize machine learning classifiers, namely Convolution Neural Netw…
YOLOv4 (v3/v2) - Windows and Linux version of Darknet Neural Networks for object detection (Tensor Cores are used)
Complete, simple and cool convolutional neural network framework, built from scratch, parallel able with OpenMP and almost dependency free. Supports custom architectures.
SpMV-CNN: A set of convolutional neural nets for estimating the run time and energy consumption of the sparse matrix-vector product
Mobilenet v1 trained on Imagenet for STM32 using extended CMSIS-NN with INT-Q quantization support
A minimalist Deep Learning framework for embedded Computer Vision
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