يعرض 221 - 240 نتائج من 396 نتيجة بحث عن '(( data processing algorithm ) OR ((( developing novel algorithm ) OR ( element data algorithm ))))', وقت الاستعلام: 0.13s تنقيح النتائج
  1. 221

    Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

    منشور في 2025
    "…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …"
  2. 222

    Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter حسب Mena S. ElMenshawy (17983807)

    منشور في 2023
    "…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …"
  3. 223

    A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security حسب S. Shitharth (12017480)

    منشور في 2023
    "…Therefore, the proposed work intends to implement a group of novel methodologies for developing an effective Cyborg intelligence security model to secure smart city systems. …"
  4. 224

    A survey and comparison of wormhole routing techniques in a meshnetworks حسب Al-Tawil, K.M.

    منشور في 1997
    "…These multiprocessing systems consist of processing elements or nodes which are connected together by interconnection networks in various topologies. …"
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    article
  5. 225

    A multi-pretraining U-Net architecture for semantic segmentation حسب Cagla Copurkaya (22502042)

    منشور في 2025
    "…The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …"
  6. 226

    Structural similarity evaluation between XML documents and DTDs حسب Tekli, J.

    منشور في 2007
    "…The automatic processing and management of XML-based data are ever more popular research issues due to the increasing abundant use of XML, especially on the Web. …"
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    conferenceObject
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    Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements حسب Emara-Shabaik, Husam

    منشور في 2020
    "…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. The nonlinear element is assumed to be of the polynomial type with known order; The identification is based on input/output data where the output is contaminated with measurement noise. …"
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    article
  11. 231

    Competitive learning/reflected residual vector quantization for coding angiogram images حسب Mourn, W.A.H.

    منشور في 2003
    "…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …"
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    article
  12. 232

    Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves حسب S. Andhale, Yogesh

    منشور في 2018
    "…The TOA data of the wave reflected from the damage is used in the two arrival time difference and astroid algorithms to locate the damage in an enclosed area. …"
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    Sentiment Analysis for Arabic Social media Movie Reviews Using Deep Learning حسب MEZAHEM, FATEMA HAMAD

    منشور في 2022
    "…For sentiment analysis, pre-processing is a crucial step in the data preparation process. …"
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  18. 238

    A novel hybrid methodology for fault diagnosis of wind energy conversion systems حسب Khaled Dhibi (16891524)

    منشور في 2023
    "…Feature selection pre-processing is an important step to increase the accuracy of the classification algorithm and decrease the dimensionality of a dataset. …"
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    On the complexity of multi-parameterized cluster editing حسب Abu-Khzam, Faisal

    منشور في 2017
    "…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …"
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    article