MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba

A Swift library that uses the Accelerate framework to provide high-performance functions for matrix math, digital signal processing, and image manipulation.

Imaging is a simple image processing package for Go

带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step

Vulkan/CUDA/HIP/OpenCL/Level Zero/Metal Fast Fourier Transform library

A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.

[Unofficial] PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)

Library for specialized dense and sparse matrix operations, and deep learning primitives.

An implementation of the system-wide JamesDSP audio processing engine for non-rooted Android devices

Image processing and manipulation in JavaScript

Understanding Convolution for Semantic Segmentation

Building Convolutional Neural Networks From Scratch using NumPy

Tensorflow implementation of Gated Conditional Pixel Convolutional Neural Network

Audio DSP effects build on Android system framework layer. This is a repository contains a pack of high quality DSP algorithms specialized for audio processing.

Deep Learning in C#

Implementation of 1D, 2D, and 3D FFT convolutions in PyTorch. Much faster than direct convolutions for large kernel sizes.

A discrete-time Python-based solver for the Stochastic On-Time Arrival routing problem

ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels

Efficient Haskell Arrays featuring Parallel computation