Search Results - (( image classification parallel algorithm ) OR ( java implementation tree 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
    “…The low-level features such as edges, blobs, and ridges were extracted for grouping and classification. Object recognition and image classification comes after the wavelet transform. …”
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  2. 2
    CUDA implementation of fractal image compression

    CUDA implementation of fractal image compression by Al Sideiri A., Alzeidi N., Al Hammoshi M., Chauhan M.S., AlFarsi G.

    Published 2023
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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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
    Combining deep and handcrafted image features for MRI brain scan classification

    Combining deep and handcrafted image features for MRI brain scan classification by Hasan, Ali M., Jalab, Hamid A., Meziane, Farid, Kahtan, Hasan, Al-Ahmad, Ahmad Salah

    Published 2019
    “…More recently, the application of deep learning algorithms to medical imaging leads to impressive performance enhancements in classifying and diagnosing complicated pathologies, such as brain tumors. …”
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  6. 6
    Human gait recognition and classification using similarity index for various conditions

    Human gait recognition and classification using similarity index for various conditions by Makhdoomi, Nahid A., Gunawan, Teddy Surya, Habaebi, Mohamed Hadi

    Published 2013
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  7. 7
    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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  8. 8
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  9. 9
    Human gait recognition and classification using similarity index for various conditions

    Human gait recognition and classification using similarity index for various conditions by Makhdoomi, Nahid A., Gunawan, Teddy Surya, Habaebi, Mohamed Hadi

    Published 2013
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  10. 10
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  11. 11
    Fpga-Based Accelerator For The Identification Of Finger Vein Pattern Via K-Nearest Centroid Neighbors

    Fpga-Based Accelerator For The Identification Of Finger Vein Pattern Via K-Nearest Centroid Neighbors by Yew , Tze Ee

    Published 2016
    “…KNCN is a type of classification technique in image processing which involves calculation of centroid and sorting of K-nearest centroid neighbors. …”
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  12. 12
    Square patch feature based face detection architecture for high resolution smart camera

    Square patch feature based face detection architecture for high resolution smart camera by Mohd Mustafah, Yasir, Bigdeli, Abbas, Azman, Amelia Wong, Lovell, Brian

    Published 2010
    “…From The simulation result shows that the proposed face detection architecture could speed up the equivalent software based face detector up to 12 times. Parallelizing the feature classification modules could improve the performance further.…”
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  13. 13
    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    “…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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  14. 14
    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    “…The first stage is preprocessing procedure that combines the thresholding and filtering algorithm for pre processing the MRI images while the second stage contains two phases of main processing techniques of enhancement and segmentation. …”
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