يعرض 1 - 20 نتائج من 21 نتيجة بحث عن '(( spatialized from learning algorithm ) OR ( spatialized _ learning algorithm ))', وقت الاستعلام: 0.11s تنقيح النتائج
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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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    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
    "…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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    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
    "…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …"
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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
    "…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …"
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    Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction حسب Syed Mohammad (21075689)

    منشور في 2025
    "…The application of machine learning (ML) and deep learning (DL) models in the field of toxicity has gained burgeoning interest. …"
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    Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting حسب Abdelkader Baggag (16864140)

    منشور في 2019
    "…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …"
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    EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach حسب Muhammad Adeel Asghar (6724982)

    منشور في 2019
    "…The pre-trained AlexNet model is used to extract the raw features from the 2D Spectrogram for each channel. To reduce the feature dimensionality, spatial, and temporal based, bag of deep features (BoDF) model is proposed. …"
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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
    "…<p dir="ltr">Studying the spatial and temporal evolution in turbulent flames represents one of the most challenging problems in the combustion community. …"
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    Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach حسب Mohammad Taghi Dabiri (16904658)

    منشور في 2023
    "…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …"
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    From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors حسب Michael R. Giordano (9976173)

    منشور في 2021
    "…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. …"
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    Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... حسب Elmahdy, Samy

    منشور في 2020
    "…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …"
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