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What is RunMat?

RunMat eliminates MATLAB license costs while delivering faster performance. Teams can run existing .m scripts and workflows without rewriting code or purchasing per-seat licenses. GPU acceleration is automatic -- no code changes required. Engineers get results up to 131x faster than NumPy on dense numerical workloads, accelerating parameter sweeps, simulations, and data processing pipelines. Deploys anywhere: desktop (Windows, macOS, Linux), browser (no install needed), CI/CD pipelines, and Jupyter notebooks. Single portable binary with no dependencies. MIT licensed with no seat limits. Ideal for engineering teams in signal processing, controls, quantitative finance, imaging, and scientific computing who need high-performance numerical tools without proprietary license overhead.

What is MatConvNet?

The open source library VLFeat provides an extensive selection of renowned algorithms aimed at computer vision, excelling in tasks like image understanding and the matching and extraction of local features. Its diverse set of algorithms includes Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, the agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, and large scale SVM training, among others. Written in C for optimal performance and compatibility, it features MATLAB interfaces that improve user accessibility and is supported by detailed documentation. This library works seamlessly across various operating systems such as Windows, Mac OS X, and Linux, which enhances its usability across multiple platforms. Furthermore, the MatConvNet toolbox is specifically crafted for MATLAB, focusing on the implementation of Convolutional Neural Networks (CNNs) for a range of computer vision tasks. Renowned for its user-friendliness and efficiency, MatConvNet allows for the execution and training of advanced CNNs, offering numerous pre-trained models suited for applications like image classification, segmentation, face detection, and text recognition. The synergistic use of these powerful tools delivers a comprehensive framework that supports researchers and developers in advancing their projects in computer vision, ensuring they are equipped with cutting-edge resources and capabilities. This combination fosters innovation within the field by enabling seamless experimentation and development.

Media

Media

Integrations Supported

GitHub
Jupyter Notebook
MATLAB
npm

Integrations Supported

API Availability

API Availability

Pricing Information

$0
Free, Open Source. MIT licensed runtime with no seat limits. Cloud plans available for collaboration and team features.
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

RunMat

Date Founded

2022

Company Location

United States

Company Website

runmat.com

Company Facts

Organization Name

VLFeat

Company Location

United States

Company Website

www.vlfeat.org/matconvnet/

Categories and Features

Computer-Aided Engineering (CAE)

Fluid Dynamics
Import / Export Files
Manufacturing Process Simulation
Mechanical Event Simulation
Thermal Analysis

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation

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