يعرض 1 - 20 نتائج من 44 نتيجة بحث عن '(( elementi per algorithms ) OR ((( spatial modeling algorithm ) OR ( neural coding algorithm ))))', وقت الاستعلام: 0.15s تنقيح النتائج
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    Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams حسب Eduardo Feo-Flushing (23276023)

    منشور في 2021
    "…Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. …"
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    CoLoSSI: Multi-Robot Task Allocation in Spatially-Distributed and Communication Restricted Environments حسب Ishaq Ansari (22047902)

    منشور في 2024
    "…<p dir="ltr">In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consist of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. …"
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    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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    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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    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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    Geographical Area Network—Structural Health Monitoring Utility Computing Model حسب Hasan Tariq (18131842)

    منشور في 2019
    "…Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. …"
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    Performance comparison of variable-stepsize IMEX SBDF methods on advection-diffusion-reaction models حسب Raed Ali Mara'Beh (17337892)

    منشور في 2025
    "…<p>Advection-diffusion-reaction (ADR) models describe transport mechanisms in fluid or solid media. …"
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    Performance comparison of variable-stepsize IMEX SBDF methods on advection-diffusion-reaction models حسب Raed Ali Ayesh Marabeh (21142247)

    منشور في 2025
    "…<p dir="ltr">Advection-diffusion-reaction (ADR) models describe transport mechanisms in fluid or solid media. …"
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    Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends حسب Abdellatif M. Sadeq (16931841)

    منشور في 2024
    "…In addition, the possible minimum and maximum values of responses at the corresponding operating parameters are found using a genetic algorithm (GA) approach. Model 1 could capture the computational fluid dynamics (CFD) outputs with high precision at different flame radiuses and time instants with a maximum absolute error percentage of 5.46%. …"