New Algorithms for Deep Learning Machines by unknown

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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…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. …”

Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

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Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…Data-driven approaches, such as machine learning (ML), particularly deep learning (DL), have shown promising results. …”
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Deep and transfer learning for building occupancy detection: A review and comparative analysis by Aya Nabil Sayed (17317006)

“…This article provides an in-depth survey of the strategies used to analyze sensor data and determine occupancy. The article’s primary emphasis is on reviewing deep learning (DL), and transfer learning (TL) approaches for occupancy detection. …”

Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu by Ayesha Atif (22155133)

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Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…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 by Albayari, Reem

“…Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

“…The application of machine learning (ML) and deep learning (DL) models in the field of toxicity has gained burgeoning interest. …”

Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…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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Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Classifying Maqams of Qur'anic Recitations Using Deep Learning by Shahriar, Sakib

Subjects: “…Deep learning…”
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security by Muhammad Maaz (5600600)

“…Consequently, the proposed hybrid deep learning anomaly detection approaches not only enhance IoT security but also provide a robust control system for addressing emerging multivariate cyber threats.…”

Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning by Amer, Hala Nagi

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Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks by Mohammed Almehdhar (22046597)

“…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. …”

A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

“…Our results provide some findings regarding how deep learning models can be used to improve text classification research in Arabic language.…”
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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

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Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. …”