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يعرض 201 - 220 نتائج من 461 نتيجة بحث عن '(((( data processing algorithm ) OR ( deep learning algorithm ))) OR ( element network algorithm ))', وقت الاستعلام: 0.13s تنقيح النتائج
  1. 201

    Sentiment visualization of correlation of loneliness mapped through social intelligence analysis حسب Hurmat Ali Shah (18192889)

    منشور في 2024
    "…Social media platforms have become a valuable source of data to study this phenomenon.</p><h3>Objectives</h3><p dir="ltr">This paper aims to visualize the frequency of loneliness-related themes and topics in Twitter data. …"
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    Fuzzy simulated evolution algorithm for topology design of campusnetworks حسب Youssef, H.

    منشور في 2000
    "…We present an approach based on the simulated evolution algorithm for the design of campus network topology. …"
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    article
  9. 209

    MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection حسب Sui Paul Ang (18460605)

    منشور في 2023
    "…<p dir="ltr">Accurate detection of pedestrian lanes is a crucial criterion for vision-impaired people to navigate freely and safely. The current deep learning methods have achieved reasonable accuracy at this task. …"
  10. 210

    Recent Advances of Chimp Optimization Algorithm: Variants and Applications حسب Daoud, Mohammad Sh.

    منشور في 2023
    "…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …"
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    Data redundancy management for leaf-edges in connected environments حسب Mansour, Elio

    منشور في 2022
    "…Major advances in the fields of Internet and Communication Technology (ICT), data modeling/processing, and sensing technology have rendered traditional environments (e.g., cities, buildings) more connected. …"
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    article
  13. 213

    Artificial Intelligence for Skin Cancer Detection: Scoping Review حسب Abdulrahman Takiddin (14153181)

    منشور في 2021
    "…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…"
  14. 214

    A hybrid graph representation for recursive backtracking algorithms حسب Abu-Khzam, Faisal N.

    منشور في 2017
    "…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …"
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    conferenceObject
  15. 215

    The effects of data balancing approaches: A case study حسب Paul Mooijman (4453189)

    منشور في 2023
    "…Our results showed that the replacement method was effective, and LogisticRegression combined with the oversampling algorithms SMOTE or ADASYN, GaussianProcessClassifier with the oversampling algorithm SMOTE, and LinearDiscriminantAnalysis were the best performing models after log transformation of the dataset was followed by Recursive Feature Elimination.…"
  16. 216

    Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE حسب Mathew, Elezabeth

    منشور في 2020
    "…Various descriptive, diagnostic, predictive, and prescriptive analysis is done on the e-procurement data. The deep learning model developed can perform thousands of routine and, repetitive tasks within a fairly short period compared to what it would take for a human being without any compromise on the quality of work. …"
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  17. 217

    DAP: A dataset-agnostic predictor of neural network performance حسب Sui Paul Ang (18460605)

    منشور في 2024
    "…This task often must be repeated many times, especially when developing a new deep learning algorithm or performing a neural architecture search. …"
  18. 218

    Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information حسب M. Ghoniem, Rania

    منشور في 2019
    "…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …"
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