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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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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022Subjects: Get full text
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Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection
Published 2022“…This review is an update on recent contributions utilizing novel sensing technologies over the past five years which include electrocardiogram, electromagnetic, bioimpedance, photoplethysmography, and acceleration measures as well as bodily fluid glucose sensors to monitor glucose and trend detection. We also review methods that use machine learning algorithms to predict blood glucose trends, especially for high risk events such as hypoglycemia. …”
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Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks
Published 2024“…Nowadays, deep learning algorithms are essential for ensuring the reliable, safe, and efficient operation of these complex energy systems. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”
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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…A sizable dataset of electronic text data was gathered from multiple social media platforms like Twitter, Instagram, YouTube, and many more sites in order to examine cyberbullying in social media using machine learning and deep learning techniques. The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis
Published 2023“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis
Published 2023“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education
Published 2022“…This paper proposes a new deep learning method to detect student emotions. The main aim of this paper is to map the relationship between teaching practices and student learning based on emotional impact. …”
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Deep and transfer learning for building occupancy detection: A review and comparative analysis
Published 2022“…The article’s primary emphasis is on reviewing deep learning (DL), and transfer learning (TL) approaches for occupancy detection. …”
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A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
Published 2025“…Given that Android applications are frequent targets for malware, ensuring the integrity of FL-based malware detection systems is critical. We introduce an attack framework that integrates Genetic Algorithms (GA) with two prominent adversarial techniques, namely, the Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD), specifically designed for FL environments. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Published 2024“…Lastly, a newly improved learning algorithm encompasses a modified pelican optimization algorithm (MOD-POA) and an extreme learning machine (ELM) for classification tasks. …”
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Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks
Published 2024“…This survey paper offers an in-depth examination of advanced machine learning (ML) and deep learning (DL) approaches employed in developing sophisticated IDS for safeguarding IVNs against potential cyber-attacks. …”
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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
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