Search Results - parallel using ((deep algorithm) OR (drops algorithm))*

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  1. 1
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  2. 2
    The feature parallelism model of visual recognition

    The feature parallelism model of visual recognition by Hassan, Marwa Yousif, Shuriye, Abdi Omar, Hassan Abdalla Hashim, Aisha, Salami, Momoh Jimoh Eyiomika, Khalifa, Othman Omran

    Published 2017
    “…Training time for feature parallelism model has dropped to 21% less than that of Deep Face. …”
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  3. 3
    Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha

    Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha by Mustapha, Muhammad Firdaus

    Published 2018
    “…Self-organizing Map (SOM) is a very popular algorithm that has been used as clustering algorithm and data exploration. …”
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  4. 4
    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering

    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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  5. 5
    A parallel-model speech emotion recognition network based on feature clustering

    A parallel-model speech emotion recognition network based on feature clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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  6. 6
    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks

    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

    Published 2022
    “…In this paper, a parallel deep learning-based community detection method in large complex networks (CNs) is proposed. …”
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  7. 7
    Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE)

    Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE) by Alias, Norma, Islam, Md. Rajibul

    Published 2010
    “…This study focuses on the implementation of parallel algorithm for the simulation of tumor growth using two dimensional Helmholtz’s wave equation on a distributed parallel computing system. …”
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  8. 8
    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery

    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Sim, Seera, Manjeevan, Chee, Peng Lim

    Published 2023
    “…Accordingly, this paper proposes a new parallel ensemble model comprising hybrid machine and deep learning for undertaking FDD tasks. …”
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  9. 9
    Improving parallel Self-organizing Map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha

    Improving parallel Self-organizing Map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha by Mustapha, Muhammad Firdaus

    Published 2018
    “…Self-organizing Map (SOM) is a very popular algorithm that has been used as clustering algorithm and data exploration. …”
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  10. 10
    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
    “…In parallel, handcrafted features are extracted using the modified gray level co-occurrence matrix (MGLCM) method. …”
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  11. 11
    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living

    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Motwakel, Abdelwahed, Elhameed, Elmouez Samir Abd, Osman, Mohammed, Kumar, Arun, Singla, Chinu, Munjal, Muskaan

    Published 2024
    “…Natural Language Processing (NLP) with Deep Learning (DL) for Tweets Classification includes use of advanced neural network designs to analyse and classify Twitter messages. …”
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  12. 12
    A novel neuroscience-inspired architecture: for computer vision applications

    A novel neuroscience-inspired architecture: for computer vision applications by Hassan, Marwa Yousif, Khalifa, Othman Omran, Abu Talib, Azhar, Olanrewaju, Rashidah Funke, Hassan Abdalla Hashim, Aisha

    Published 2016
    “…The validation of the proposed model was conducted using “Shape” feature dimension. The results show up to 2% accuracy rate compared to our implementation of DeepFace, a high performing face recognition algorithm that was developed by Facebook, is achieved under the same hardware/ software conditions; and we were able to speed up the training up to 21% per a training patch compared to DeepFace.…”
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    Proceeding Paper
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  13. 13
    Online simulation to monitor multiphase flow using laser source as transmitter

    Online simulation to monitor multiphase flow using laser source as transmitter by Naizatul Shima, Mohd Fadzil, Ruzairi, Abdul Rahim, Juliza, Jamaludin, Mohd Hafiz, Fazalul Rahiman, Siti Zarina, Muji, Yasmin, Abdul Wahab

    Published 2021
    “…Linear Back-projection (LBP) is the algorithm that is used to reconstruct the image in real-time. …”
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  14. 14
    Online Simulation To Monitor Multiphase Flow Using Laser Source As Transmitter

    Online Simulation To Monitor Multiphase Flow Using Laser Source As Transmitter by Naizatul Shima Mohd Fadzil, Ruzairi Abdul Rahim, Mohd Hafiz Fazalul Rahiman, Siti Zarina Muji, Yasmin Abdul Wahab, Juliza Jamaludin

    Published 2024
    journal::journal article
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  15. 15
    Performance monitoring algorithm for optimizing electrical power generated by using photovoltaic system

    Performance monitoring algorithm for optimizing electrical power generated by using photovoltaic system by Pradeep, M.V.K., Balbir, S.M.S., Norani, M.M.

    Published 2016
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  16. 16
    An Efficient Energy Aware Adaptive System-On-Chip Architecture For Real-Time Video Analytics

    An Efficient Energy Aware Adaptive System-On-Chip Architecture For Real-Time Video Analytics by Ahmed, Hisham Ahmed Ali

    Published 2016
    “…A Performance model for Zynq is developed using analytical method and used in hardware/software codesign to facilitate algorithms mapping to hardware. …”
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  17. 17
    An integrated priority-based cell attenuation model for dynamic cell sizing

    An integrated priority-based cell attenuation model for dynamic cell sizing by Amphawan, Angela, Omar, Mohd Nizam, Din, Roshidi

    Published 2012
    “…Real-time predicted mobile traffic from the EFuNN structure was used to control the size of all the cells.Results obtained demonstrate the robustness of the integrated module in recognizing the temporal pattern of the mobile traffic and dynamically controlling the cell size in order to reduce the number of calls dropped.…”
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  18. 18
    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
    “…Preprocessing techniques based on CSI are applied to improve the feature extraction from the amplitude data in an indoor environment. 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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