Showing 19 open source projects for "pattern recognition"

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  • 1
    audioFlux

    audioFlux

    A library for audio and music analysis, feature extraction

    A library for audio and music analysis, and feature extraction. Can be used for deep learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. audioflux is a deep learning tool library for audio and music analysis, feature extraction. It supports dozens of time-frequency analysis transformation methods and hundreds of corresponding time-domain and frequency-domain feature combinations. It can be provided to deep learning networks for training and is used to study various tasks in the audio field such as Classification, Separation, Music Information Retrieval(MIR) ASR, etc.
    Downloads: 2 This Week
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  • 2
    Armadillo

    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
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    Downloads: 2,679 This Week
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  • 3
    pattern_classification

    pattern_classification

    A collection of tutorials and examples for solving machine learning

    The pattern_classification repository is an educational project that provides tutorials, examples, and reference materials related to machine learning and statistical pattern recognition. The project aims to help learners understand the process of building predictive models by presenting structured explanations and practical examples. It includes notebooks and guides that demonstrate data preprocessing, feature extraction, model training, and evaluation techniques used in machine learning workflows. ...
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  • 4
    Bandicoot

    Bandicoot

    fast C++ library for GPU linear algebra & scientific computing

    * Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code
    Downloads: 4 This Week
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  • 5
    LSTMs for Human Activity Recognition

    LSTMs for Human Activity Recognition

    Human Activity Recognition example using TensorFlow on smartphone

    ...The repository includes data preprocessing scripts, neural network architecture definitions, and training pipelines that allow researchers to reproduce and modify the experiments. It serves as an educational example of how deep learning models can process temporal sensor signals for pattern recognition tasks.
    Downloads: 0 This Week
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  • 6
    Pattern Recognition and Machine Learning

    Pattern Recognition and Machine Learning

    Repository of notes, code and notebooks in Python

    Pattern Recognition and Machine Learning is an open-source repository that provides Python implementations and interactive notebooks for algorithms presented in the book Pattern Recognition and Machine Learning by Christopher Bishop. The project recreates many of the mathematical concepts and diagrams from the book using executable Jupyter notebooks, allowing readers to experiment directly with the algorithms described in the text.
    Downloads: 0 This Week
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  • 7
    Gluon CV Toolkit

    Gluon CV Toolkit

    Gluon CV Toolkit

    ...It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection, semantic segmentation and pose estimation, to instance segmentation and video action recognition. The model zoo is the one-stop shopping center for many models you are expecting. GluonCV embraces a flexible development pattern while is super easy to optimize and deploy without retaining a heavyweight deep learning framework.
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  • 8
    CDF-TS
    ...This software is under GNU General Public License version 3.0 (GPLv3) This code is a demo of method described by the following publication: Zhu, Y., Ting, K.M., Carman, M. and Angelova, M., 2021, April. CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities. Pattern Recognition. https://doi.org/10.1016/j.patcog.2021.107977 The preprint version can be obtained at: https://arxiv.org/abs/1810.02897
    Downloads: 0 This Week
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  • 9
    Clustering by Shared Subspaces

    Clustering by Shared Subspaces

    Grouping Points by Shared Subspaces for Effective Subspace Clustering

    These functions implement a subspace clustering algorithm, proposed by Ye Zhu, Kai Ming Ting, and Mark J. Carman: "Grouping Points by Shared Subspaces for Effective Subspace Clustering", Published in Pattern Recognition Journal at https://doi.org/10.1016/j.patcog.2018.05.027
    Downloads: 0 This Week
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  • 10

    DGRLVQ

    Dynamic Generalized Relevance Learning Vector Quantization

    Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different...
    Downloads: 0 This Week
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  • 11
    Density-ratio based clustering

    Density-ratio based clustering

    Discovering clusters with varying densities

    ...An existing density-based clustering algorithm, which is applied to the rescaled dataset, can find all clusters with varying densities that would otherwise impossible had the same algorithm been applied to the unscaled dataset. Reference: Zhu, Y., Ting, K. M., & Carman, M. J. (2016). Density-ratio based clustering for discovering clusters with varying densities. Pattern Recognition. http://www.sciencedirect.com/science/article/pii/S0031320316301571
    Downloads: 0 This Week
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  • 12

    Fingerprint Recognition System

    Fingerprint Recognition System 5.3 - Matlab source code

    The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a...
    Downloads: 1 This Week
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  • 13

    libVMR

    VMR - machine learning library

    ...libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from data sets. Typical applications here are pattern recognition ( binary classification).
    Downloads: 0 This Week
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  • 14

    ProximityForest

    Efficient Approximate Nearest Neighbors for General Metric Spaces

    ..., WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer Vision and Pattern Recognition, 2012. This source code is provided without warranty and is available under the GPL license. More commercially-friendly licenses may be available. Please contact Stephen O'Hara for license options. Please view the wiki on this site for installation instructions and examples on reproducing the results of the papers.
    Downloads: 0 This Week
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  • 15

    jaf_Kernels

    Similarity Word-Sequence Kernels for Sentence Clustering toolkit

    This project implements the techniques used in this paper: @INPROCEEDINGS{Andres10a, author = {Jesús Andrés-Ferrer and Germán Sanchis-Trilles and Francisco Casacuberta}, title = {Similarity Word-Sequence Kernels for Sentence Clustering}, booktitle = {Proceedings of the 8th International Workshop on Statistical Pattern Recognition}, year = {2010}, } This project depends on jaf_Utils: http://sourceforge.net/projects/jafutils/ Install it prior installation of jaf_Kernels.
    Downloads: 0 This Week
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  • 16
    PyPR - Python Pattern Recognition. A small collection of useful pattern recognition methods. The code is still in its early stages.
    Downloads: 0 This Week
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  • 17
    Stochastico is an implementation of stochastic discrimination for pattern recognition, predictive modeling and data mining applications.
    Downloads: 0 This Week
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  • 18
    ALiVE
    A tool that helps develope the course of cognitive thought processes through software. This tool will look at the raw hex code of any input. It establishes pattern recognition over a mesured time incrament that in itself is at a different pace.
    Downloads: 0 This Week
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  • 19
    Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
    Downloads: 0 This Week
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