يعرض 41 - 60 نتائج من 116 نتيجة بحث عن '(( element data algorithm ) OR ((( spatial modeling algorithm ) OR ( data mining algorithm ))))', وقت الاستعلام: 0.11s تنقيح النتائج
  1. 41

    Sentiment analysis for Arabizi in social media. (c2015) حسب Tobaili, Taha

    منشور في 2015
    "…Yalla 7abibi, it is very useful to have a data mining tool that can analyze the sentiment of Twitter users in the Arab world. …"
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    masterThesis
  2. 42

    STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization حسب Muhammad Salman Khan (7202543)

    منشور في 2025
    "…In this paper, a novel speech separation algorithm is proposed that integrates the twin-delayed deep deterministic (TD3) policy gradient reinforcement learning (RL) agent with the expectation maximization (EM) algorithm for clustering the spatial cues of individual sources separated on azimuth. …"
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    Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification حسب Rajendra Babu Chikkala (22330876)

    منشور في 2025
    "…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …"
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    Recent Advances of Chimp Optimization Algorithm: Variants and Applications حسب Daoud, Mohammad Sh.

    منشور في 2023
    "…The review paper will be helpful for the researchers and practitioners of ChOA belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining, and clustering. As well, it is wealthy in research on health, environment, and public safety. …"
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    MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

    منشور في 2022
    "…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …"
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    Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction حسب Syed Mohammad (21075689)

    منشور في 2025
    "…It is noted that spatial relationships within molecules are crucial in predicting hERG blockers. …"
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    Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms حسب Almahmood, Mothanna

    منشور في 2023
    "…Our study aimed to use data mining classification techniques, in order to classify the individual into two categories: user or non-user. …"
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    XBeGene: Scalable XML Documents Generator by Example Based on Real Data حسب Harazaki, Manami

    منشور في 2012
    "…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …"
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    conferenceObject
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    Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach حسب Arshad Ali Khan (23152516)

    منشور في 2025
    "…To mitigate overfitting, we implemented dropout layers, batch normalization, and early stopping, significantly enhancing the model’s generalization capability. Specifically, three different open-access datasets were combined into a single training dataset, capturing extensive temporal, spatial, and environmental variability. …"
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    Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

    منشور في 2023
    "…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"