Open Source MATLAB Software Development Software
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MATLAB Software Development Software
View 6125 business solutionsBrowse free open source MATLAB Software Development Software and projects below. Use the toggles on the left to filter open source MATLAB Software Development Software by OS, license, language, programming language, and project status.
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Octave Forge
A collection of packages providing extra functionality for GNU Octave
Octave Forge is a central location for collaborative development of packages for GNU Octave. The Octave Forge packages expand Octave's core functionality by providing field specific features via Octave's package system. See https://octave.sourceforge.io/packages.php for a list of all available packages. GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. The Octave language is quite similar to Matlab so that most programs are easily portable. Refer to https://www.octave.org for more information. -
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GNSS-SDR
An open source software-defined GNSS receiver
An open source software-defined Global Navigation Satellite Systems (GNSS) receiver written in C++ and based on the GNU Radio framework. -
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MATLAB and Simulink for Students
An awesome list of helpful resources for students learning MATLAB
Are you a new MATLAB user seeking helpful tips and tricks? Are you a member of a student society in search of engaging workshops? Or perhaps you're looking for opportunities to test your MATLAB skills through student competitions or challenges? Look no further! Our awesome list repository below is a resource that caters to all these needs. Whether you're starting from scratch or aiming to enhance your existing knowledge, you'll find a wealth of information to help you learn MATLAB and make progress on your journey as a student. Explore the repository now and unlock the potential of MATLAB. -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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EIDORS (electrical impedance and diffuse optical tomography reconstruction software) provides software, algorithms and reference data for image reconstruction and modelling.
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Exclusively Dark Image Dataset
ExDARK dataset is the largest collection of low-light images
The Exclusively Dark (ExDARK) dataset is one of the largest curated collections of real-world low-light images designed to support research in computer vision tasks under challenging lighting conditions. It contains 7,363 images captured across ten different low-light scenarios, ranging from extremely dark environments to twilight. Each image is annotated with both image-level labels and object-level bounding boxes for 12 object categories, making it suitable for detection and classification tasks. The dataset was created to address the lack of large-scale low-light datasets available for research in object detection, recognition, and enhancement. It has been widely used in studies of low-light image enhancement, deep learning approaches, and domain adaptation for vision models. Researchers can also explore its associated source code for low-light image enhancement tasks, making it an essential resource for advancing work in night-time and low-light visual recognition. -
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PlatEMO
Evolutionary multi-objective optimization platform
Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. Most of them are representative algorithms published in top journals after 2010. Users can select various figures to be displayed, including the Pareto front of the result, the Pareto set of the result, the true Pareto front, and the evolutionary trajectories of any performance indicator values. PlatEMO provides a powerful and friendly GUI, where users can configure all the settings and perform experiments in parallel via the GUI without writing any code. -
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NTU RGB-D
Info and sample codes for "NTU RGB+D Action Recognition Dataset"
The “NTU RGB+D” repository provides access to a large-scale dataset for human action recognition (and its extension, NTU RGB+D 120). The dataset includes multiple modalities (RGB video, depth sequences, infrared video, 3D skeletal joint data) captured with multiple Kinect v2 cameras simultaneously. The repository also contains MATLAB / Python demo scripts for loading, visualizing, and processing skeleton data, mapping between modalities, and handling dataset structure. Multi-modal action recognition dataset, RGB, depth, infrared, skeletal data. Split into background / evaluation sets for one-shot evaluation (in the extended dataset). -
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cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that can be adapted for custom datasets, making it useful for experimenting with retrieval systems in computer vision. By leveraging CNN architectures, the project showcases how learned embeddings can capture semantic similarity across varied images. This resource serves as both an educational reference and a foundation for further exploration in image retrieval research.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with modifications tailored for face detection tasks. It includes training scripts, evaluation code, and pre-trained models that achieve strong results on popular benchmarks such as AFW, PASCAL Face, FDDB, and WIDER FACE. The framework is optimized for speed and accuracy, making it suitable for both academic research and practical applications in computer vision. -
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Face Verification Experiment
Original Caffe Version for LightCNN-9. Highly recommend to use PyTorch
face_verification_experiment is a research repository focused on experiments in face verification using deep learning. It provides implementations and scripts for testing different neural network architectures and training strategies on face recognition and verification tasks. The project is designed to help researchers and practitioners evaluate the performance of models on standard datasets and explore techniques for improving accuracy. By offering experimental setups, it enables reproducibility and comparative study of face verification approaches. The repository serves as a resource for understanding the application of convolutional neural networks to identity verification, highlighting both methodology and results. It is primarily intended for academic and research purposes in computer vision and biometrics. -
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
The Grey Wolf Optimizer for Path Planning is a MATLAB-based implementation of the Grey Wolf Optimizer (GWO) algorithm designed for UAV path and trajectory planning. It allows simulation of both two-dimensional and three-dimensional UAV trajectory planning depending on parameter setups. The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. It includes progress visualization to help monitor the optimization process during simulations. Users can adjust objective function weights and experiment with multiple heuristic search strategies to explore optimal solutions. This project demonstrates applications in multi-agent and multi-UAV cooperative path planning, making it useful for research and educational purposes in the field of intelligent optimization and robotics. -
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Kalibr Allan
IMU Allan standard deviation charts
kalibr_allan is a utility repository that provides scripts and tools for calculating IMU noise parameters for use in Kalibr and other IMU filtering systems. While manufacturers typically provide “white noise” values in IMU datasheets, the bias instability and random walk parameters must be determined experimentally. This project enables users to compute those values using Allan variance analysis from recorded IMU data. The workflow involves recording IMU measurements with the device stationary, converting ROS bag files into MATLAB-compatible formats, and then running MATLAB scripts to generate Allan deviation plots. These plots are analyzed to determine noise density and random walk parameters for both gyroscopes and accelerometers. The repository also includes example data and plots from real sensors such as the XSENS MTI-G-700, Tango Yellowstone Tablet, and ASL-ETH VI-Sensor, providing reference points for interpretation. -
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MBeautifier
MBeautifier is a MATLAB source code formatter, beautifier
MBeautifier is a lightweight M-Script-based MATLAB source code formatter usable directly in the MATLAB Editor. -
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Omniglot
Omniglot data set for one-shot learning
This repository hosts the Omniglot dataset for one-shot learning, containing handwritten characters across multiple alphabets along with stroke data. It includes both MATLAB and Python starter scripts (e.g. demo.m, demo.py) to illustrate how to load the images and stroke sequences and run baseline experiments (such as classification by modified Hausdorff distance). The dataset provides both an image representation of each character and the time-ordered stroke coordinates ([x, y, t]) for each instance. Includes stroke data (time-sequenced coordinates) per sample. The repository is intended as a benchmark dataset in few-shot / meta-learning research, not as a plug-and-play detection or classification engine. Pre-split “background” and “evaluation” alphabets for standard benchmarking. -
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Plotly Graphing Library for MATLAB
Plotly Graphing Library for MATLAB
Create interactive charts in your web browser with MATLAB® and Plotly. -
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SuiteSparse
The official SuiteSparse library: a suite of sparse matrix algorithms
The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University. -
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segyio
Fast Python library for SEGY files
Segyio is a small LGPL-licensed C library for easy interaction with SEG-Y and Seismic Unix formatted seismic data, with language bindings for Python and Matlab. Segyio is an attempt to create an easy-to-use, embeddable, community-oriented library for seismic applications. Features are added as they are needed; suggestions and contributions of all kinds are very welcome. -
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Continuation Core and Toolboxes (COCO)
Toolboxes for parameter continuation and bifurcation analysis.
Development platform and toolboxes for parameter continuation, e.g., bifurcation analysis of dynamical systems and constrained design optimization. This material is based upon work partially supported by the National Science Foundation under Grant No. 1016467 and the Danish research council (FTP) under the project number 0602-00753B. Any opinions, findings, and conclusions or recommendations expressed on this site are those of the authors and do not necessarily reflect the views of the National Science Foundation or other funding sources. Documentation and tutorials are available for the following toolboxes: * ep : continuation and bifurcations of equilibrium points * coll : continuation of constrained collections of trajectory segments, including multi-segment boundary-value problems * po : continuation and bifurcations of periodic orbits in smooth and hybrid systems * recipes : collection of examples from the book Recipes for Continuation -
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IBEX_MDA
An open infrastructure software to facilitate radiomics research.
This web page is not guaranteed to have the latest versions. The latest stand-alone version can be downloaded at http://bit.ly/IBEX_MDAnderson The latest source-code version can be downloaded at http://bit.ly/IBEXSrc_MDAnderson IBEX (imaging biomarker explorer) is an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. IBEX software package was developed using the MATLAB and C/C++ programming languages. The software architecture deploys the modern model-view-controller, unit testing, and function handle programming concepts to isolate each quantitative imaging analysis task, to validate if their relevant data and algorithms are fit for use, and to plug in new modules. -
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MATLABStarter
Dynamically creates MATLAB path and updates code repositories
A startup function for MATLAB that dynamically adds MATLAB m files, Java folders and .jar archives in user-defined folders and optionally updates any subversion or git working copies found. -
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Commodity class to facilitate interaction between MATLAB and Bitplane Imaris via COM or ICE interface.
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gnumex
Compile matlab mex files with gcc on Windows Platforms
Gnumex is a package that allows Matlab mex and engine files written in C, C++, Fortran 77 or Fortran 95 to be compiled with MinGW (or Cygwin) MS Windows versions of gcc, gfortran or g95. NOTE: Newer versions of Matlab now natively support Mingw, negating the need for this package. -
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BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.
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This project aims to develop a colour-based vision processing system for use in RoboCup. We are using a CCD camera for input to an FPGA. The system locates coloured objects and outputs detected corners.