Showing 36 of 130 projects
A dataflow compiler for quantized neural network inference on FPGAs, generating highly efficient custom accelerators.
Fast multilayer perceptron neural network library for iOS and Mac OS X using Apple's Accelerate Framework.
A Go interface for importing and executing pre-trained ONNX neural network models without framework dependencies.
MatLab/Octave implementations of popular machine learning algorithms with detailed mathematical explanations and code examples.
A convolutional neural network program that identifies inverted Chinese character captchas used by Zhihu for login verification.
TensorFlow implementation of character-aware neural language models using CNN, highway networks, and LSTM.
A lightweight C library for building and training small to medium artificial neural networks with minimal dependencies.
A deep learning library built on Chainer for molecular property prediction using graph convolutional neural networks.
A tensor library for differentiable functional programming in F#, with PyTorch-like APIs and GPU support.
Classify music genre from a 10-second audio stream using a convolutional neural network trained on mel-frequency spectrograms.
A simplified Keras-like framework for PyTorch that reduces boilerplate code for training neural networks.
A command-line tool for neural network inference using Unix pipeline philosophy.
A Go library implementing feedforward/backpropagation neural networks with support for multiple activation functions, solvers, and classification modes.
Ruby gem providing bindings to FANN (Fast Artificial Neural Network) for building and training neural networks.
A real-time, uncertainty-aware deep learning model for semantic segmentation of 3D LiDAR point clouds in autonomous driving.
A parallel deep learning framework written in modern Fortran for training and inference of dense, convolutional, and transformer networks.
A lightweight C++ machine learning library designed for embedded electronics and robotics applications.
OCaml bindings for PyTorch, providing NumPy-like tensor computations with GPU acceleration and automatic differentiation.
An AI-powered captcha solver using SimGAN to generate synthetic training data without manual labeling.
A lightweight neural network for near-real-time semantic segmentation of LiDAR point clouds using polar coordinate quantization.
A neural network playground built in pure Swift for iOS, with no third-party dependencies.
A fast neural network framework for iOS and macOS using Swift and Metal for GPU acceleration.
An easy-to-use C# deep learning library with support for multiple backends including TensorFlow, PyTorch, and CUDA/OpenCL.
A Go implementation of neural networks including BackPropagation, RBF, and Perceptron networks with parallel processing capabilities.
A feedforward neural network library for Rust implementing backpropagation training.
A Swift library providing neural networks, machine learning algorithms, and AI data structures for iOS and macOS development.
A Docker-based image annotation tool for bounding box labeling with auto-labeling support, designed for deep learning training.
A C++ neural network library for Node.js optimized for large datasets and multi-threaded training.
A lightweight neural network library for Deno with CPU, GPU, and WASM backends, designed for serverless and edge environments.
A comprehensive scientific computing and AI/ML library in pure Rust, offering SciPy-compatible APIs with 10-100x performance gains.
An iOS library that applies artistic styles to images using Core ML and pre-trained neural style transfer models.
A convolutional neural network model built with Keras for recognizing captcha images generated by the Laravel Captcha library.
A pure Crystal machine learning library for building and training neural networks with CPU/GPU support and PyTorch compatibility.
A lightweight multilayer perceptron neural network library for MicroPython, designed for embedded systems like ESP32 and Pycom modules.
An open-source CAD framework for designing, simulating, and deploying deep neural networks on embedded platforms.
.NET Standard bindings for Apache MXNet, providing C# developers with NumPy-compatible APIs for machine learning model development, training, and deployment.
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