Deep learning approach for automatic classification of ocular and cardiac artifacts in MEG Data |
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Arabic Sign Language Characters Recognition Based on a Deep Learning Approach and a Simple Linear Classifier |
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Accurate Real-Time Traffic Sign Recognition Based on the Connected Component Labeling and the Color Histogram Algorithms |
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Towards Offline Arabic Handwritten Character Recognition Based on Unsupervised Machine Learning Methods: A Perspective Study |
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Towards Arabic Alphabet and Numbers Sign Language Recognition |
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Towards Accurate Real-Time Traffic Sign Recognition Based on Unsupervised Deep Learning of Spatial Sparse Features: A Perspective |
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Wearable Devices, Smartphones, and Interpretable Artificial Intelligence in Combating COVID-19 |
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Application of Unsupervised Machine Learning Classification for the Analysis of Driver Behavior in Work Zones in the State of Qatar |
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A Recommendation System for Selecting the Appropriate Undergraduate Program at Higher Education Institutions Using Graduate Student Data |
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Newborn Cry-Based Diagnostic System to Distinguish between Sepsis and Respiratory Distress Syndrome Using Combined Acoustic Features |
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Infant Cry Signal Diagnostic System Using Deep Learning and Fused Features |
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Wearable Devices and Explainable Unsupervised Learning for COVID-19 Detection and Monitoring |
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Employment Recommendation System for Graduates Using Machine Learning |
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Survival Prediction of Children after Bone Marrow Transplant Using Machine Learning Algorithms |
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On the Utilization of Emoji Encoding and Data Preprocessing with a Combined CNN-LSTM Framework for Arabic Sentiment Analysis |
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Transformer-Based Approach to Pathology Diagnosis Using Audio Spectrogram |
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A tree-based explainable AI model for early detection of Covid-19 using physiological data |
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Exploring the Impact of Image-Based Audio Representations in Classification Tasks Using Vision Transformers and Explainable AI Techniques |
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Integrating Statistical Methods and Machine Learning Techniques to Analyze and Classify COVID-19 Symptom Severity |
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