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A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs
Published 2024“…To showcase the performance of such algorithms, we propose two approaches for the task of teeth diagnosis utilizing Orthopantomograms (panoramic radiographs): 1) a direct classification approach; and 2) a hybrid approach that combines a deep learning model with a traditional classifier. …”
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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review
Published 2023Subjects: -
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A machine learning model for early detection of diabetic foot using thermogram images
Published 2021“…A comparatively shallow CNN model, MobilenetV2 achieved an F1 score of ∼95% for a two-feet thermogram image-based classification and the AdaBoost Classifier used 10 features and achieved an F1 score of 97%. …”
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Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review
Published 2023Subjects: -
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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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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…However, traditional monitoring methods can be labor-intensive and costly, especially in complex underwater environments. Deep learning approaches have made significant progress in digital image processing, particularly in object recognition and classification, and are among the most popular computer vision tools. …”
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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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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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Design and implementation of a deep learning-empowered m-Health application
Published 2023“…In the first phase, the corresponding image is extracted and sent to a web service. Later, the web service classifies using the pre-trained model built based on a deep learning algorithm. …”
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