Enhancement of two-dimensional holographic images by resolutionimprovement through hologram aperture expansion by Abdel-Aal, R.E.

“…Due to the 1-D nature of the algorithm, different predictive models used for rows and columns in the case of 2-point and similar objects; which calls for some prior knowledge of the object geometry. …”
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A multi-pretraining U-Net architecture for semantic segmentation by Cagla Copurkaya (22502042)

“…In this research, we propose and evaluate a modified version of a deep learning algorithm called U-Net architecture for partitioning histopathological images. …”

DAP: A dataset-agnostic predictor of neural network performance by Sui Paul Ang (18460605)

“…This task often must be repeated many times, especially when developing a new deep learning algorithm or performing a neural architecture search. …”

Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives by Yassine Himeur (14158821)

Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review by Francisco Monteiro-Guerra (16864122)

Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity by Abdullah Al Siam (22304047)

“…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …”

Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice by Turker Tuncer (16677966)

“…The artificial neural network (ANN), support vector machine (SVM) and deep learning models, especially the convolutional neural network (CNN), are the most commonly used machine learning approaches where they proved to be performance in most cases. …”

Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review by Daksh Dave (17949239)

Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks by Bekir Sait Ciftler (17541801)

“…We implement a simulation environment to benchmark the proposed distributed DRL-based method against other methods such as Q-Learning (QL) and Deep Q-Networks (DQN), and centralized heuristic power allocation algorithms. …”

Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”

DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs by Bahareh Jafari (22501715)

“…As such, in addition to avoiding coverage holes, we should also make the outage time as small as possible. By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …”

Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation by Raveendra Pilli (21633287)

Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier by JAIN, SWETA

“…The preprocessed images are segmented with hybrid Fuzzy C Means (FCM) and Gaussian Mixture Model (GMM) which partition the image into sub groups to make it easier for classification by reducing the complexity. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli (20748758)

“…<p dir="ltr">Glaucoma is defined as progressive optic neuropathy that damages the structural appearance of the optic nerve head and is characterized by permanent blindness. For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”

Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review by Alaa Abd-alrazaq (17058018)

Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine by Majd A. AbuAlrob (22392505)

“…<p>Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhancing diagnostic precision, and enabling personalized treatment. Machine learning and deep learning technologies improve seizure monitoring, automate EEG analysis, and facilitate tailored therapeutic strategies, addressing the complexities of epilepsy management. …”

A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks by Yassine Himeur (14158821)

“…Experimental results on simulated and real datasets collected at two regions, which have extremely different climate conditions, confirm that the proposed deep micro-moment architecture outperforms other machine learning algorithms and can effectively detect anomalous patterns. …”

XBeGene: Scalable XML Documents Generator by Example Based on Real Data by Harazaki, Manami

“…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
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