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

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

Imaging is a simple image processing package for Go

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

Understanding Convolution for Semantic Segmentation

Tensorflow implementation of Gated Conditional Pixel Convolutional Neural Network

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

Building Convolutional Neural Networks From Scratch using NumPy

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

Deep Learning in C#

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

Efficient Haskell Arrays featuring Parallel computation

ShuffleNet in PyTorch. Based on https://arxiv.org/abs/1707.01083

Caffe for Sparse Convolutional Neural Network

Simple demonstration of separable convolutions

Image processing and manipulation in JavaScript

The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers

Expression Templates Library (ETL) with GPU support

Efficient Sparse-Winograd Convolutional Neural Networks (ICLR 2018)

python implementation of efficient convolution operators for tracking

Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.

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.

Vulkan Fast Fourier Transform library

[ECCV 2020] PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer

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

Xilinx Deep Learning IP

A Cross-platform Library for Swift

This python code performs an efficient speech reverberation starting from a dataset of close-talking speech signals and a collection of acoustic impulse responses.

ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics

Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, and clause indexing