Network Threat Detection Using Machine/Deep Learning in SDN-Based Platforms: A Comprehensive Analysis of State-of-the-Art Solutions, Discussion, Challenges, and Future Research Dir... by Naveed Ahmed (2433958)

“…Much work has been done on NIDS but there are still improvements needed in reducing false alarms and increasing threat detection accuracy. Recently advanced approaches such as deep learning (DL) and machine learning (ML) have been implemented in SDN-based NIDS to overcome the security issues within a network. …”

Evaluation of Pre-Trained CNN Models for Geographic Fake Image Detection by Hadid, Abdenour

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Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review by Asma Alamgir (18288895)

Exploiting the Spatio-Temporal Patterns in IoT Data to Establish a Dynamic Ensemble of Distributed Learners by Mehdi Mohammadi (5024105)

“…This increase is 82% less than the 11.3 increase seen in the baseline model. …”

Ensemble Stacking Model for Sentiment Analysis of Emirati and Arabic Dialects by A. Al Shamsi, Arwa

“…Then, an ensemble stacking model was introduced to combine the best-performing deep learning models used in this study. The ensemble stacking deep learning model consisted of deep learning models with a meta learner layer of classifiers. …”
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Visual Sentiment Analysis from Disaster Images in Social Media by Syed Zohaib Hassan (18387129)

“…<div><p>The increasing popularity of social networks and users’ tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. …”

Blood Glucose Regulation Modelling and Intelligent Control by Nasar, Nabeel

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Electric Grid Resilience Enhancement During Natural Disasters: An Optimization-Based UAV Inspection and Dynamic Crew Dispatch Model by Serag, Yousef

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Artificial Intelligence for Detecting and Quantifying Fatty Liver in Ultrasound Images: A Systematic Review by Fahad Muflih Alshagathrh (18427950)

Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Robust Prediction of Wildfire Spread in Australia by Michael Palk (17947841)

In-Between Projection Interpolation in Cone-Beam CT Imaging using Convolutional Neural Networks by Dweek, Samaa

“…In this work, an interpolation method based on Convolutional Neural Networks (CNN) is proposed to generate new in-between projections to increase the overall number of projections used in 4D-CBCT reconstruction. …”
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Theft Detection Unit For Photo-Votaic Generation in Smart Grid Networks by Almadani, Nouf Ahmad

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Electrochemical Studies on the Corrosion Behavior of Common Metals in Eutectic Ionic Liquids by Alhasan, Rami

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

The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data by Alaa Awad Abdellatif (17151163)

“…<p dir="ltr">Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. …”

Decoding silent speech: a machine learning perspective on data, methods, and frameworks by Adiba Tabassum Chowdhury (19444792)

“…Examining state-of-the-art SSR frameworks, the paper covers important topics such signal processing, feature extraction, ML techniques for decoding and optimizing and assessing the performance of SSR models. We emphasize how deep learning (DL) and ML models have evolved to increase SSR resilience and accuracy. …”

Intelligent scaling for 6G IoE services for resource provisioning by Abdullah Alharbi (4173502)

“…IScaler is considered to be made for MEC in Deep Reinforcement Learning (DRL). The paper has considered several requirements for making service placement decisions. …”

Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities by Md Golam Morshed (19420537)

“…One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant increase in feature learning-based representations for action recognition has emerged in recent years, due to the widespread use of deep learning-based features. …”