Enables MATLAB Drive on your computer and provides an integrated experience in MATLAB

Install the MinGW-w64 C/C++ compiler for Windows

Try new Beta features including dark theme, updated layout, expanded search capabilities, and more.

Pretrained AlexNet network model for image classification

Pretrained Resnet-50 network model for image classification

Import, export, process, and visualize hyperspectral data

Pretrained GoogLeNet network model for image classification

Tools to compile a real-time application that runs on a Speedgoat target computer

Pretrained VGG-16 network model for image classification

Build, Simulate, and Run Quantum Algorithms

Use the GUIDE to App Designer Migration tool to help transition your GUIDE apps to App Designer.

Model, simulate, and analyze wireless communications networks

Neural Network Toolbox Model for ResNet-18 Network

Import and export TensorFlow models within MATLAB

Import and export ONNX™ models within MATLAB for interoperability with other deep learning frameworks

Pretrained VGG-19 network model for image classification

Use OpenCV algorithms in MATLAB

Pretrained MobileNet-v2 model for image classification

Quantize and Compress Deep Learning models

Interface for Deep Learning Libraries from MATLAB Coder

Pretrained Resnet-101 network model for image classification

Detect objects using a pretrained YOLO v4 object detection network trained on COCO dataset.

Pretrained Inception-v3 network model for image classification

Pretrained DenseNet-201 network model for image classification

Simulate and verify agile RF transceivers and predict impact of RF imperfections using test signals

Generate and decode frames and waveforms of ZigBee and UWB

Simulink integration for Unreal Engine 4

Import pretrained PyTorch models into MATLAB

Pretrained YOLO v3 model for object detection.

Interface for Deep Learning Libraries from GPU Coder

A collection of standard drive cycles (vehicle speed vs. time)

View and Explore a 3D Volumetric Chest Scan

Use Visual Studio Code to view and debug C and C++ code, in combination with supported MATLAB and Simulink workflows.

Communicate with instruments that use IVI or VXIplug&play drivers

Pretrained EfficientNet-b0 model for image classification

Robot model library to visualize and simulate robots with MATLAB and Simulink

Pretrained ShuffleNet model for image classification

Pretrained Xception model for image classification

Pretrained NasNet-Mobile network model for image classification

This support package allows you to customize scenes in the Unreal^® Editor and use them in Simulink^®.

Simulate additional mixed-signal systems with Simulink and Mixed-Signal Blockset

Pretrained SqueezeNet model for image classification

Pretrained DarkNet-53 network model for image classification

Pretrained NasNet-Large network model for image classification

Pretrained DarkNet-19 network model for image classification

Model, simulate, analyze, and visualize CubeSats using Aerospace Blockset

Verify and test robustness of deep learning networks

Ephemeris Data for Aerospace Toolbox

Model and simulate spatially-defined channels for multi-user MIMO wireless systems

Pretrained Inception-ResNet-v2 network model for image classification

Visualize and Analyze Deep Learning Networks

Manage, configure and analyze variants in your system with Variant Manager for Simulink package.

Generate C code for single and multicore devices on bare metal, RTOS, and middleware services

Simulate 3GPP 5G radio technologies

Pretrained GoogLeNet network trained on Places365 data set for image classification

Customize scenes in Unreal^® Editor for co-simulation of autonomous flight algorithms in Simulink^®

Algorithms to simulate Unmanned Aerial Vehicles (UAVs) and connect to hardware

Geoid Data for Aerospace Toolbox

Incorporate pre-trained TensorFlow Lite (TFLite) models into MATLAB and Simulink applications for simulation and deployment to hardware.

Simplify adoption and optimize Continuous Integration/Continuous Delivery (CI/CD) workflows for Simulink