Open Source MATLAB Artificial Intelligence Software - Page 4
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MATLAB Artificial Intelligence Software
View 13749 business solutionsBrowse free open source MATLAB Artificial Intelligence Software and projects below. Use the toggles on the left to filter open source MATLAB Artificial Intelligence Software by OS, license, language, programming language, and project status.
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Image Fusion
Deep Learning-based Image Fusion: A Survey
This repository is a survey / code collection centered on deep learning–based image fusion (e.g. fusing infrared + visible light images, multi-modal fusion) methods. It catalogs many fusion algorithms (e.g. DenseFuse, FusionGAN, NestFuse, etc.), links to code implementations, and describes evaluation metrics. The repository includes a “General Evaluation Metric” subfolder containing objective fusion metrics. It is not a single monolithic tool, but rather a curated reference and aggregation of methods, code and performance comparisons in the domain of image fusion. Survey style description of method taxonomy, architectures, loss types. Compilation of many state-of-the-art image fusion methods (infrared + visible, multi-focus, multi-exposure). Survey style description of method taxonomy, architectures, loss types. -
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Isolation Similarity
aNNE similarity based on Isolation Kernel
Demo of using aNNE similarity for DBSCAN. Written by Xiaoyu Qin, Monash University, March 2019, version 1.0 This software is under GNU General Public License version 3.0 (GPLv3) This code is a demo of method described by the following publication: Qin, X., Ting, K.M., Zhu, Y. and Lee, V.C., 2019, July. Nearest-neighbour-induced isolation similarity and its impact on density-based clustering. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 4755-4762). https://ojs.aaai.org//index.php/AAAI/article/view/4402 Bibtex format: @inproceedings{qin2019nearest, title={Nearest-neighbour-induced isolation similarity and its impact on density-based clustering}, author={Qin, Xiaoyu and Ting, Kai Ming and Zhu, Ye and Lee, Vincent CS}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, volume={33}, pages={4755--4762}, year={2019} } -
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Isolation‐based anomaly detection
Isolation‐based anomaly detection using nearest‐neighbor ensembles
This site provides the source code of Isolation‐based anomaly detection (iNNE). https://onlinelibrary.wiley.com/doi/abs/10.1111/coin.12156 Bandaragoda, T.R., Ting, K.M., Albrecht, D., Liu, F.T., Zhu, Y. and Wells, J.R., 2018. Isolation‐based anomaly detection using nearest‐neighbor ensembles. Computational Intelligence, 34(4), pp.968-998. -
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KLT-IV v1.0 has been designed to offer a user-friendly graphical user interface for the determination of river flow velocity and river discharge using videos acquired using a variety of fixed and moving platforms. KLT-IV employs optical flow and computer vision techniques for the tracking of features present on the river surface with pixel displacements being converted to real-world velocities using an optimised camera model approach. Movement of the platform can be accounted for when ground control points and/or stable features are present, or where the platform is equipped with GPS and IMU sensors. Please direct queries or comments to: https://groups.google.com/forum/#!forum/klt-iv-image-velocimetry-software
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LRSLibrary
Low-Rank and Sparse Tools for Background Modeling and Subtraction
LRSLibrary is a MATLAB library offering a broad collection of low-rank plus sparse decomposition algorithms, primarily aimed at background/foreground modeling from videos (background subtraction) and related computer vision tasks. Compatibility across MATLAB versions (tested in R2014–R2017) The library includes matrix and tensor methods (over 100 algorithms) and has been tested across MATLAB versions from R2014 onward. The algorithms can also be adapted to other computer vision or machine learning problems beyond video. Large algorithm collection: > 100 matrix- and tensor-based low-rank + sparse methods. Open-source license, documentation and references included. -
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Linear Time Invariant (LTI) system identification using particle swarm optimization (PSO) algorithm. Creators : Vahid Kiani, Hadi Sadoghi Yazdi
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LWPR
Locally Weighted Projection Regression (LWPR)
Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite: [1] Sethu Vijayakumar, Aaron D'Souza and Stefan Schaal, Incremental Online Learning in High Dimensions, Neural Computation, vol. 17, no. 12, pp. 2602-2634 (2005). [2] Stefan Klanke, Sethu Vijayakumar and Stefan Schaal, A Library for Locally Weighted Projection Regression, Journal of Machine Learning Research (JMLR), vol. 9, pp. 623--626 (2008). More details and usage guidelines on the code website. -
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mex-svm is a set of patches against SVM-Light to compile into "mex" libraries and enable fast Support Vector Machine evaluation from within MATLAB.
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A MATLAB spectral clustering package to handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. We implement various ways of approximating the dense similarity matrix, including nearest neighbors and the Nystrom method.
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MCTIMME
Microbial Counts Trajectories Infinite Mixture Model Engine
MCTIMME is a nonparametric Bayesian computational framework for analyzing microbial time-series data.The current implementation is in Matlab. -
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MILT is designed to facilitate research in imitation learning through first-person computer games. Featuring strategic, tactical and reactive modules, it allows developers to work with their preferred games or take advantage of integrated Quake2 support.
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MPT is a toolbox that supplies cross-platform libraries for real-time perception primitives, including face detection, eye detection, blink detection, and color tracking.
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MTCNN Face Detection Alignment
Joint Face Detection and Alignment
MTCNN_face_detection_alignment is an implementation of the “Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks” algorithm. The algorithm uses a cascade of three convolutional networks (P-Net, R-Net, O-Net) to jointly detect faces (bounding boxes) and align facial landmarks in a coarse-to-fine manner, leveraging multi-task learning. Non-maximum suppression and bounding box regression at each stage. The repository includes Caffe / MATLAB code, support scripts, and instructions for dependencies. Non-maximum suppression and bounding box regression at each stage. Online hard sample mining to improve training robustness. -
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Machine Learning Homework
Matlab Coding homework for Machine Learning
The Machine-Learning-homework repository by user “Ayatans” is a collection of MATLAB code intended to solve or illustrate assignments in machine learning courses. It includes implementations of standard machine learning algorithms (such as regression, classification, etc.), scripts for data loading and preprocessing, and evaluation routines (e.g. accuracy, error metrics). Because it is structured as homework or practice material, the code is likely intended more for didactic use than for production deployment. It may contain comments, example datasets, and perhaps test scripts. The repository does not seem to be heavily maintained as a software project; rather, it functions as a library of solved problems and educational examples. The project is useful if you want working MATLAB examples of classic ML techniques, to study, adapt, or compare with your own implementations. -
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This site contains four packages of Mass and mass-based density estimation. 1. The first package is about the basic mass estimation (including one-dimensional mass estimation and Half-Space Tree based multi-dimensional mass estimation). This packages contains the necessary codes to run on MATLAB. 2. The second package includes source and object files of DEMass-DBSCAN to be used with the WEKA system. 3. The third package DEMassBayes includes the source and object files of a Bayesian classifier using DEMass. DEMassBayes.7z has jar file to be used with WEKA and a readme file listing parameters used. The source files are included in DEMassBayes_Source.7z. 4. The four package is MassTER includes source and JAR file to be used with WEKA system..
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Mass-based dissimilarity
A data dependent dissimilarity measure based on mass estimation.
This software calculates the mass-based dissimilarity matrix for data mining algorithms relying on a distance measure. References: Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure. KDD 2016 http://dx.doi.org/10.1145/2939672.2939779 The source code, presentation slide and poster are attached under "Files". The presentation video in KDD 2016 is published on https://youtu.be/eotD_-SuEoo . Since this software is licensed under the Gnu General Public license GPLv3, any derivative work must be licensed under the GPL as well. This software is free only for non-commercial use. For commercial projects, it is possible to obtain a commercial license through the Commercial Services of Federation University Australia. Please email the first author of the original paper tingkm@nju.edu.cn for any inquiries about this software. -
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Matlab Community Detection Toolbox
CDTB is a MATLAB toolbox which performs Community Detection
We present the Community Detection Toolbox (CDTB), a MATLAB toolbox which can be used to perform community detection. The CDTB contains several functions from the following categories. 1. graph generators; 2. clustering algorithms; 2. cluster number selection functions; 4. clustering evaluation functions. Furthermore, CDTB is designed in a parametric manner so that the user can add his own functions and extensions. The CDTB can be used in at least three ways. The user can employ the functions from the MATLAB command line; or he can write his own code, incorporating the CDTB functions; or he can use the Graphical User Interface (GUI) which automates the community detection and includes some data visualization options. -
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MatlabMachine
Machine learning algorithms
Matlab-Machine is a comprehensive collection of machine learning algorithms implemented in MATLAB. It includes both basic and advanced techniques for classification, regression, clustering, and dimensionality reduction. Designed for educational and research purposes, the repository provides clear implementations that help users understand core ML concepts. -
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Mexopencv
Collection and a development kit of matlab mex functions for OpenCV
mexopencv is a collection of MEX functions that provide MATLAB bindings for OpenCV, the popular computer vision library. It enables MATLAB users to access nearly the full range of OpenCV’s C++ API directly from MATLAB, combining the ease of MATLAB scripting with the performance of OpenCV. -
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Matlab and Octave code to fit a mixture of Gaussians with covariance regularization to data using EM update rules.
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Netvlad
NetVLAD: CNN architecture for weakly supervised place recognition
NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets. -
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The project goal is to develop several IP cores that would implement artificial neural networks using FPGA resources. These cores will be designed in such a way to allow easy integration in the Xilinx EDK framework.
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NodeWeaver is a tool for generating SystemML Neuronal Networks from Neuronal Network descriptions (these technologies are nascent, so no links yet...). Intended use is to generate SystemML NNs for later execution using a SystemML simulator (e.g. BRAHMS).
