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41
Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
Published 2022Subjects: -
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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review
Published 2023Subjects: -
44
Estimating Construction Project Duration Using a Machine Learning Algorithm
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masterThesis -
45
Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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masterThesis -
46
An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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Editorial on the Special Section on Algorithms, Circuits, and Systems for Signal Processing at the Edge
Published 2021“…<p dir="ltr">Technological trends alongside with the unprecedented growth of the data generated by devices sparsely distributed, most of them mobile devices, cannot be supported by traditional approaches and processing systems. …”
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
Published 2023“…However, they might not perform as expected, take much time in training, or not have enough input data to generalize well. To that end, deep transfer learning (DTL) and deep domain adaptation (DDA) have recently been proposed as promising solutions to alleviate these issues. …”
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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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51
Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018)
Published 2018“…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …”
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masterThesis -
52
A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates
Published 2024“…A new Hamiltonian semi-analytical method is established to investigate the free vibration characteristics of piezoelectric multilayered plates. …”
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53
Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022“…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …”
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54
A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…This study not only examines the well-known challenges such as limited availability of data but provides a novel, structured taxonomy of deep learning techniques tailored for the monitoring of seagrass, highlighting their unique advantages and limitations within diverse marine environments. …”
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Towards Scalable Process Mining Pipelines
Published 2023“…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …”
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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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Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…Hence, detecting any act of cyberbullying in an automated manner will be helpful for stakeholders to prevent any unfortunate results from the victim’s perspective. Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
doctoralThesis -
60