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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
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doctoralThesis -
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Design of adaptive arrays based on element position perturbations
Published 1993“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. The actions and rewards for the proposed algorithm are selected carefully to guide the agent to its objective. …”
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
Published 2023“…While artificial intelligence (AI) smooths the path of computers to think like humans, machine learning (ML) and deep learning (DL) pave the way more, even by adding training and learning components. …”
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Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Data-driven approaches, such as machine learning (ML), particularly deep learning (DL), have shown promising results. …”
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Stacking-based ensemble learning for remaining useful life estimation
Published 2023“…In this study, predictive models that estimate the remaining useful life of turbofan engines have been developed using deep learning algorithms on NASA’s turbofan engine degradation simulation dataset. …”
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Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
Published 2025“…<p dir="ltr">This study presents an innovative solution for simultaneous energy optimization and dynamic yaw control of all-wheel-drive (AWD) electric vehicles (EVs) using deep reinforcement learning (DRL) techniques. To this end, three model-free DRL-based methods, based on deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and TD3 enhanced with curriculum learning (CL TD3), are developed for determining optimal yaw moment control and energy optimization online. …”
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A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…A range of machine learning (ML) methods can be used to recognize facial expressions based on data from small to large datasets. …”
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Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”
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Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers
Published 2022“…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …”
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Hybrid Deep Learning-based Models for Crop Yield Prediction
Published 2022“…In this study, we developed deep learning-based models to evaluate how the underlying algorithms perform with respect to different performance criteria. …”
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Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…This is in contrast to previous approaches where GA is applied to the whole sequence. The proposed method is compared with previous GA-based approaches. …”
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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…The increase in imagery data has in turn created a demand for automated detection and classification using deep neural network-based techniques. This study reviews the current deep-learning techniques used for monitoring and classification of the seagrass. …”
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Machine Learning-based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction
Published 2024“…Methods: Several state-of-the-art pre-trained deep learning models, used for video frame interpolation, are utilized in this work to generate intermediary projections. …”
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An efficient approach for textual data classification using deep learning
Published 2022“…Next, we employ machine learning algorithms: logistic regression, random forest, K-nearest neighbors (KNN), and deep learning algorithms: long short-term memory (LSTM), artificial neural network (ANN), and gated recurrent unit (GRU) for classification. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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