Search Results for "matlab code for image classification using svm" - Page 2

Showing 40 open source projects for "matlab code for image classification using svm"

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  • 1
    ConvNet Burden

    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. Estimation of memory consumption (e.g. feature map sizes,...
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  • 2

    JSiteDescriptor

    Binding site descriptor generation for SVM based classification.

    A set of java programs that extract coordinate and chemical information from PDB files. The binding site regions are extracted using grid based scheme. For binding site, spatio-chemical descriptor is generated based on PocketMatch algorithm of Dr. Kalidas (author of this project too).
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  • 3
    Brain imaging software produced by the Brain Research Imaging Centre of The University of Edinburgh.
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  • 4
    EasyPR

    EasyPR

    An easy, flexible, and accurate plate recognition project

    EasyPR is an open-source license plate recognition system designed to detect and recognize vehicle license plates from images using computer vision and machine learning techniques. The project focuses primarily on recognizing Chinese license plates but also demonstrates general approaches to automatic number plate recognition systems. Built on top of the OpenCV computer vision library, EasyPR provides algorithms for detecting license plate regions in images, segmenting characters, and...
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  • 5
    HashingBaselineForImageRetrieval

    HashingBaselineForImageRetrieval

    Various hashing methods for image retrieval and serves as the baseline

    This repository provides baseline implementations of deep supervised hashing methods for image retrieval tasks using PyTorch. It includes clean, minimal code for several hashing algorithms designed to map images into compact binary codes while preserving similarity in feature space, enabling fast and scalable retrieval from large image datasets.
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  • 6
    F-Tracker3D

    F-Tracker3D

    A software tool for tracking fluorescent cells in 3D

    ...F-Tracker3D is written in MATLAB (©, The MathWorks, Inc., Massachusetts, USA) and the source code is freely provided. Requirements: MATLAB 2015a and Image Processing Toolbox 9.2 or later versions.
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  • 7
    MATLAB code to identify specific colors of your choice in an image, using MATLAB. Visit letsrobo.wordpress.com for detailed working of the code.
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  • 8
    Netvlad

    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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  • 9

    classify-20-NG-with-4-ML-Algo

    Problem involves classifying 20000 messages into different 20 classes

    ...Each of these algorithms has its peculiar data format; the specific format and how to reconstruct the entire dataset are illustrated in other sections below. Out of all the methods, SVM using the Libsvm [1] produced the most accurate and optimized result for its classification accuracy for the 20 classes. All the algorithm implementation was written Matlab. Download the code and Report here.
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  • 10
    IBEX_MDA

    IBEX_MDA

    An open infrastructure software to facilitate radiomics research.

    ...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.
    Downloads: 1 This Week
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  • 11
    ConvNetJS

    ConvNetJS

    Deep learning in Javascript to train convolutional neural networks

    ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and...
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  • 12
    BudgetedSVM

    BudgetedSVM

    BudgetedSVM: A C++ Toolbox for Large-scale, Non-linear Classification

    We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classi fication problems with millions of...
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  • 13
    Code for Semi-Supervised Machine Learning Techniques, Self-Learning and Co-training used in the paper: Rania Ibrahim, Noha A. Yousri, Mohamed A. Ismail and Nagwa M, El-Makky. “miRNA and Gene Expression based Cancer Classification using Self-Learning and Co-Training Approaches”. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 495-498, 2013. --------------------------------------------------------------------------- For Self-Learning: java -jar -Xms1700m SelfLearner.jar [trainFile] [testFile] [labelFile] [unlabeledFile] [Alpha] [ClassifierType(randomforest,svm)] [resultFile] [ClassifierModelFile] For Co-Training: java -jar -Xms2500m CoTraining.jar [trainFile-Side1] [testFile-Side1] [labelFile-Side1] [unlabeledFile-Side1] [trainFile-Side2] [testFile-Side2] [labelFile-Side2] [unlabeledFile-Side2] [MappingFile] [Alpha] [ClassifierType(randomforest,svm)] [resultFile] [ClassifierModelFileSide1] [ClassifierModelFileSide2]
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  • 14
    VOC-DPM

    VOC-DPM

    Object detection system using deformable part models (DPMs)

    The VOC-DPM repository is an implementation of an object detection system built on deformable part models (DPMs) and latent SVM learning, specifically packaged as “voc-release5.” It is the companion code for Ross Girshick’s dissertation, and extends earlier work on discriminatively trained DPMs. The system supports a grammar-based representation for object models, allowing structures such as mixtures and hierarchies to represent parts and whole objects. It implements both latent SVM training...
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  • 15
    OSU SVM is a Support Vector Machine (SVM) toolbox for the MATLAB numerical environment. The toolbox is used to create models for regression and classification using support vector machines.
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