Showing 561 - 580 results of 836 for search 'Computer network Security features.', query time: 0.15s Refine Results
  1. 561

    A Deep Learning Framework for Healthy Lifestyle Monitoring and Outdoor Localization by Mehrab Rafiq, Naif S. Alshammari, Haifa F. Alhasson, Dina Abdulaziz Alhammadi, Mohammed Alshehri, Ahmad Jalal, Hui Liu

    Published 2025-01-01
    “…Kernel Fisher Discriminant Analysis was applied for feature optimization, and a deep neural network was utilized for feature classification. …”
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    PENGENALAN SUARA MANUSIA MENGGUNAKAN JARINGAN SYARAF TIRUAN DENGAN METODE LINEAR PREDICTIVE CODING DAN FAST FOURIR TRANSFORM by Nirwan Sinuhaji, Benar, Romulo P. Aritonang

    Published 2023-08-01
    “…The voice signal obtained from the recording results is processed by a computer with the FFT algorithm so that a digital signal is obtained, then parsed, the results of the feature extraction with the FFT method then become the input of the LPC method and then implemented into the Artificial Neural Network. …”
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  5. 565

    Optimizing Group Activity Recognition With Actor Relation Graphs and GCN-LSTM Architectures by M. R. Tejonidhi, C. V. Aravinda, S. V. Aruna Kumar, C. K. Madhu, A. M. Vinod

    Published 2025-01-01
    “…The challenge of understanding and recognizing group activities through human behavior and interactions is a prominent issue in the realm of computer vision research. This area boasts a wide range of applications, including security surveillance, healthcare monitoring, and human-computer interaction systems. …”
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    Efficient productivity prediction model based on edge data compression in smart farms by Peng Jin, Wenshuang Du, Wenquan Jin

    Published 2025-12-01
    “…This strategy integrates lightweight edge models and region-aware clippings and compression techniques to reduce data transmission while retaining key agronomic features. Furthermore, the strategy's multi-dimensional resource-aware scheduling and optimized network multiplexing significantly enhance the efficiency of data acquisition and transmission. …”
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    HoRNS-CNN model: an energy-efficient fully homomorphic residue number system convolutional neural network model for privacy-preserving classification of dyslexia neural-biomarkers by Opeyemi Lateef Usman, Ravie Chandren Muniyandi, Khairuddin Omar, Mazlyfarina Mohamad, Ayoade Akeem Owoade, Morufat Adebola Kareem

    Published 2025-04-01
    “…Although, fully homomorphic encryption (FHE)-based methods have been proposed to maintain data confidentiality and privacy, however, existing FHE deep convolutional neural network (CNN) models still face some issues such as low accuracy, high encryption/decryption latency, energy inefficiency, long feature extraction times, and significant cipher-image expansion. …”
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