Showing 41 - 60 results of 80 for search '(((( experiments each algorithm ) OR ( element data algorithm ))) OR ( level coding algorithm ))', query time: 0.10s Refine Results
  1. 41

    Efficient Seismic Volume Compression using the Lifting Scheme by Khene, M. F.

    Published 2000
    “…Finally a runlength plus a Huffman encoding are applied for binary coding of the quantized coefficients.…”
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    Downlink channel estimation for IMT-DS by Faisal, S.

    Published 2001
    “…To obtain channel estimates during pilot symbols, we propose a chip level adaptive channel estimation which performs better than the conventional method. …”
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    Optimisation of PV Cleaning Practices: Comparison Between Performance Based and Periodic Based Approaches by ALHAJERI, RASHED ABDULLA

    Published 2018
    “…The PV output, soiling rates, electricity price, and cleaning costs were inputted into the algorithm and 5 different approaches were simulated: 1. …”
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  8. 48

    A hybrid Harris Hawks optimizer for economic load dispatch problems by Al-Betar, Mohammed Azmi

    Published 2022
    “…The results show that the proposed algorithm can achieve a significant performance for the majority of the experimented cases. …”
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  9. 49

    Defining quantitative rules for identifying influential researchers: Insights from mathematics domain by Ghulam Mustafa (458105)

    Published 2024
    “…The rules were developed for each parameter category using the Decision Tree Algorithm, which achieved an average accuracy of 70 to 75 percent for identifying awardees in mathematics domains. …”
  10. 50

    Predicting the Release of Chemotherapeutics From the Core of Polymeric Micelles Using Ultrasound by Abdel-Hafez, Mamoun

    Published 2015
    “…Finally, the optimal release estimate is obtained by probabilistically adding the estimates from the hypothesized Kalman filter estimates. The proposed algorithms are first tested using a simulation environment. …”
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  11. 51

    Clustering Tweets to Discover Trending Topics about دبي (Dubai) by ALYALYALI, SALAMA KHAMIS SALEM KHAMIS

    Published 2018
    “…After this, log results into k- mean clustering algorithm with cosine similarity to measure similarity between objects of each cluster. …”
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    Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3 by Chakar, Joseph

    Published 2020
    “…We also explore variational dropout: a technique that finds individual and unbounded dropout rates for each neural network weight. Experiments on the PASCAL VOC benchmark dataset show promising results where variational dropout combined with the most efficient YOLOv3 variant lead to an extremely sparse solution that reduces 95% of the baseline network’s parameters at a relatively small drop of 3% in accuracy.…”
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  14. 54

    Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

    Published 2024
    “…The performance level improvements are practically summarized in both the transmission and reception entities with the help of the proposed hybrid network architecture and the associated Dual Deep Network algorithm. …”
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    A Multi-Channel Convolutional Neural Network approach to automate the citation screening process by Raymon van Dinter (10521952)

    Published 2021
    “…However, the screening process is highly time-consuming and error-prone as the researchers must read each title and possibly hundreds to thousands of abstracts and full-text documents. …”
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    The Effectiveness of Supervised Machine Learning in Screening and Diagnosing Voice Disorders: Systematic Review and Meta-analysis by Ghada Al-Hussain (18295426)

    Published 2022
    “…Both methods have limited standardized tests, which are affected by the clinician’s experience and subjective judgment. Machine learning (ML) algorithms have been used as an objective tool in screening or diagnosing voice disorders. …”
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    Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

    Published 2021
    “…Different patterns or queries are initially gathered from the input SQL query log, and bootstrap samples are created. Then, for each pattern, various weak clusters are constructed via X‐means clustering and are utilized as the weak learner (clusters). …”