Search Results for "matlab optimization toolbox"
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Showing 35 open source projects for "matlab optimization toolbox"
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mTRF-Toolbox
A MATLAB package for modelling multivariate stimulus-response data
mTRF-Toolbox is a MATLAB package for modelling multivariate stimulus-response data, suitable for neurophysiological data such as MEG, EEG, sEEG, ECoG and EMG. It can be used to model the functional relationship between neuronal populations and dynamic sensory inputs such as natural scenes and sounds, or build neural decoders for reconstructing stimulus features and developing real-time applications such as brain-computer interfaces (BCIs). -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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Shogun
Unified and efficient Machine Learning since 1999
Shogun is a unified and efficient Machine Learning since 1999. Shogun is implemented in C++ and offers automatically generated, unified interfaces to Python, Octave, Java / Scala, Ruby, C#, R, Lua. We are currently working on adding more languages including JavaScript, D, and Matlab. -
Lightspeed golf course management softwareFrom tee sheet management, point of sale and payment processing to marketing, automation, reporting and more—Lightspeed is built for the pro shop, restaurant, back office, beverage cart and beyond.
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OpenOCL Matlab
Optimal control, trajectory optimization, model-predictive control.
The Open Optimal Control Library is a software framework in Matlab/Octave for modeling optimal control problem. It uses automatic differentiation and fast non-linear programming solvers. It implements direct methods. In the backend it uses CasADi and ipopt. -
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ConvNet Burden
Memory consumption and FLOP count estimates for convnets
convnet-burden is a MATLAB toolbox / script collection estimating computational cost (FLOPs) and memory consumption of various convolutional neural network architectures. It lets users compute approximate burdens (in FLOPs, memory) for standard image classification CNN models (e.g. ResNet, VGG) based on network definitions. The tool helps researchers compare the computational efficiency of architectures or quantify resource needs. -
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Toolbox
Piotr's Image & Video Matlab Toolbox
Piotr’s Image & Video MATLAB Toolbox is a general-purpose MATLAB toolbox for image and video processing and vision tasks, offering utilities, filters, detection, feature extraction, and algorithm building blocks. Example and demo scripts for usage (e.g. acfReadme, detector readmes). It augments MATLAB’s native capabilities (not replacing the Image Processing Toolbox) by providing efficient, reusable wrappers and optimized routines. -
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MatlabFunc
Matlab codes for feature learning
MatlabFunc is a collection of MATLAB functions developed by the ZJULearning group to support various tasks in computer vision, machine learning, and numerical computation. The repository brings together a wide range of utility scripts, algorithms, and implementations that serve as building blocks for research and development. These functions cover areas such as matrix operations, optimization, data processing, and visualization, making them broadly applicable across different research domains. ... -
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Rent Manager SoftwareRent Manager is award-winning property management software built for residential, commercial, and short-term-stay portfolios of any size. The program’s fully customizable features include a double-entry accounting system, maintenance management/scheduling, marketing integration, mobile applications, more than 450 insightful reports, and an API that integrates with the best PropTech providers on the market.
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mctc4bmi
Matrix and Tensor Completion for Background Model Initialization
MCTC4BMI (Multimodal Compressed Sensing and Tensor Decomposition for Brain-Machine Interfaces) is a MATLAB toolbox designed to process and analyze EEG data. It applies compressed sensing and tensor decomposition techniques to improve brain-machine interface (BMI) performance. -
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All future developments will be implemented in the new MATLAB toolbox SciXMiner, please visit https://sourceforge.net/projects/scixminer/ to download the newest version. The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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Edges
Structured Edge Detection Toolbox
Structured Edge Detection (Edges) is a MATLAB toolbox implementing the structured forests method for fast and accurate edge detection (up to ~60 fps in many settings). The toolbox also includes the Edge Boxes object proposal method, fast superpixel generation, and utilities for training, evaluation, and integration with vision pipelines. High performance (frames per second performance depending on settings). -
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LAML:Linear Algebra and Machine Learning
A stand-alone Java library for linear algebra and machine learning
LAML is a stand-alone pure Java library for linear algebra and machine learning. The goal is to build efficient and easy-to-use linear algebra and machine learning libraries. The reason why linear algebra and machine learning are built together is that full control of the basic data structures for matrices and vectors is required to have fast implementation for machine learning methods. Additionally, LAML provides a lot of commonly used matrix functions in the same signature to MATLAB, thus... -
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DeepLearnToolbox
Matlab/Octave toolbox for deep learning
DeepLearnToolbox is a MATLAB / Octave toolbox for prototyping deep learning models. It provides implementations of feedforward neural networks, convolutional neural networks (CNNs), deep belief networks (DBNs), stacked autoencoders, convolutional autoencoders, and more. The toolbox includes example scripts for each method, enabling users to quickly experiment with architectures, training, and inference workflows. -
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BPL
Bayesian Program Learning model for one-shot learning
BPL (Bayesian Program Learning) is a MATLAB implementation of the Bayesian Program Learning framework for one-shot concept learning (especially on handwritten characters). The approach treats each concept (e.g. a character) as being generated by a probabilistic program (motor primitives, strokes, spatial relationships), and inference proceeds by fitting those generative programs to a single example, generalizing to new examples, and generating new exemplars. The repository contains code for... -
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KMBOX - Kernel Methods Toolbox
A collection of kernel-based algorithms for Matlab.
KMBOX is a collection of MATLAB programs that implement kernel-based algorithms, with a focus on regression algorithms and online algorithms. It can be used for nonlinear signal processing and machine learning. -
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Java Library for Machine Learning
A pure Java library for machine learning
JML is a machine learning library in Java, it is a pure Java package, and thus is cross-platform. The goal of JML is to make machine learning methods very easy to use and speed up code conversion from MATLAB to Java. Please be noted that JML has been replaced by LAML. -
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ObjectDetector
Car Detection,Face Detectiom,Object Detection
Machine learning: This project is used for training new object like Car,Motor Cycle and so on and we use this model(xml file) for detecting in images.In this project we use viola jones algorithm. -
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An implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method for MATLAB and R. The supplied functionality includes e.g. cross-validation, kernel parameter optimization, model diagnostics and plot tools.
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BudgetedSVM
BudgetedSVM: A C++ Toolbox for Large-scale, Non-linear Classification
...We provide command-line and Matlab interfaces to BudgetedSVM, efficient API for handling large-scale, high-dimensional data sets, as well as detailed documentation to help developers use and further extend the toolbox. -
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Kernel Adaptive Filtering Toolbox
a Matlab benchmarking toolbox for kernel adaptive filtering
[Note: This project has moved. Visit https://github.com/steven2358/kafbox/ for the latest version.] A Matlab benchmarking toolbox for kernel adaptive filtering. Kernel adaptive filtering algorithms are online and adaptive regression algorithms based on kernels. They are suitable for nonlinear filtering, prediction, tracking and nonlinear regression in general. This toolbox includes algorithms, demos, and tools to compare their performance. -
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A MATLAB toolbox for simulating the movement of the iRobot Create. Contains multiple GUIs for creating maps and other input, showing the movement of the Create, and replaying a previously saved session.
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Open Genetic Algorithm Toolbox
This is a MATLAB toolbox to run a GA on any problem you want to model.
This is a toolbox to run a GA on any problem you want to model. You can use one of the sample problems as reference to model your own problem with a few simple functions. You can collaborate by defining new example problems or new functions for GA, such as scaling, selection or adaptation methods. In that case, you should then include your credits in the file, upload it to matlab central and contact the author. -
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A library analog to those included in Matlab without the need of external libraries; just right for embedded or static linking. MTL was used to build a 3d Scanner. MTL consists of pars B - Basic Functions, Matrices, Images, Hypermodels (3d Models and up) N - Numeric Functions ranging from linear regression over nonlinear optimization to singular-value computation I - Image filters and Image enhancement H - Hardware related (optional part), does require additional libraries and is only useful on certain hosts. ...
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Stanford Machine Learning Course
machine learning course programming exercise
The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy...
