Search Results - parallel extraction ((((tree algorithm) OR (bees algorithm))) OR (path algorithm))

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  1. 1
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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  2. 2
    Robust partitioning and indexing for iris biometric database based on local features

    Robust partitioning and indexing for iris biometric database based on local features by Khalaf, Emad Taha, Mohammed, Muamer N., Kohbalan, Moorthy

    Published 2018
    “…The proposed method combines three transformation methods DCT, DWT and SVD to analyse iris images and extract their local features. Further, the scalable K-means++ algorithm is used for partitioning and classification processes, and an efficient parallel technique that divides the features groups causing the formation of two b-trees based on index keys is applied for search and retrieval. …”
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  3. 3
    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title

    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…For searches and retrieval, an efficient parallel technique has been presented by dividing the group of features into two b-trees based on index keys. …”
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  4. 4
    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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  5. 5
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  6. 6
    WiFi-based human activity recognition through wall using deep learning

    WiFi-based human activity recognition through wall using deep learning by Wong, Yan Chiew, Ahmed Abuhoureyah, Fahd Saad, Mohd Isira, Ahmad Sadhiqin

    Published 2023
    “…Furthermore, a deep learning algorithm based on RNN with an LSTM algorithm is used to classify the activity instances indoors, achieving up to 97.5% accuracy in classifying seven activities. …”
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