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

“…Consequently, there is an urgent need to develop detection methods capable of distinguishing between real and fake satellite images. …”
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Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review by Asma Alamgir (18288895)

“…Artificial intelligence (AI) technologies and big data have been increasingly used to enhance the ability to predict and prepare for the patients at risk.…”

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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Challenges and practices identification in complex outsourcing relationships: A systematic literature review by Ghulam Murtaza Khan (12024573)

“…Furthermore, when compared to other types of outsourcing, complex outsourcing is extremely difficult because it necessitates a variety of control and coordination mechanisms for project management, which proportionally increases the risk of project failure. In order to overcome the failure of projects in complex outsourcing relationships, there is a need of robust systematic research to identify the key challenges and practices in this area. …”

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)

Using Mobile Technology for Coordinating Educational Plans and Supporting Decision Making Through Reinforcement Learning in Inclusive Settings by Siyam, Nur

“…Learners with special education needs and disabilities (SEND) require attention from a large set of a care team that includes parents, teachers, specialists, therapists, and doctors. …”
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Theft Detection Unit For Photo-Votaic Generation in Smart Grid Networks by Almadani, Nouf Ahmad

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

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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)

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. …”

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. …”