Evaluating machine learning technologies for food computing from a data set perspective by Nauman Ullah Gilal (17302714)

“…Food computing benefits from technologies based on modern machine learning techniques, including deep learning, deep convolutional neural networks, and transfer learning. …”

A systematic review and meta-analysis on the impact of early vs. delayed pharmacological thromboprophylaxis in patients with traumatic brain injury by Muhammad Hamza Shuja (19748620)

“…Our findings indicated that early prophylaxis significantly reduced the incidence of VTE, deep vein thrombosis (DVT), pulmonary embolism (PE), and overall mortality when compared to late administration. …”

A New Flow-Based Approach for Enhancing Botnet Detection Efficiency Using Convolutional Neural Networks and Long Short-Term Memory by Mehdi Asadi (12566741)

“…<p dir="ltr">Despite the growing research and development of botnet detection tools, an ever-increasing spread of botnets and their victims is being witnessed. …”

Food fraud detection using explainable artificial intelligence by Okan Buyuktepe (17991493)

“…<div><p>Recently, the global food supply chain has become increasingly complex, and its scalability has grown. …”

Artificial intelligence in respiratory care by Manjush Karthika (18384907)

TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images by Tawsifur Rahman (14150523)

“…Moreover, due to the increase of drug-resistant tuberculosis, the disease becomes more challenging in recent years. …”

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

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)

Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review by Hazrat Ali (421019)

“…It provides key insights into how vision transformers complemented the performance of AI and deep learning methods for lung cancer. Furthermore, the review also identifies the datasets that contributed to advancing the field.…”

Detection of Real-Time Malicious Intrusions and Attacks in IoT Empowered Cybersecurity Infrastructures by Irfan Ali Kandhro (17541876)

“…To address these issues, we propose a deep learning-based novel method to detect cybersecurity vulnerabilities and breaches in cyber-physical systems. …”

Applying Graph Neural Networks to the Decision Version of Graph Combinatorial Optimization Problems by Raka Jovanovic (17947838)

Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection by Ahmad Yaser Alhaddad (7017434)

Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)

“…We find that avatar customization correlates with increased social activity, and we are able to identify distinct visual trends among the U.S.…”

Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS by Khan, Malik Nasir Afzal

“…To improve our results and increase our dataset, we use data augmentation with a deep convolutional generative adversarial network (DCGAN). …”
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YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images by Prabu Selvam (22330264)

“…It has recently become increasingly popular to apply deep learning algorithms to the identification of ships in SAR images. …”

Hyperspectral-physiological based predictive model for transpiration in greenhouses under CO₂ enrichment by Ikhlas Ghiat (16932564)

“…Three machine learning models were investigated for transpiration modelling and prediction: deep neural networks (DNN), extreme gradient boosting (XGBoost), and support vector machine regression (SVR). …”

YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm by Prabu Selvam (22330264)

MEFood: A Large-Scale Representative Benchmark of Quotidian Foods for the Middle East by Mohammed Yusuf Ansari (16904523)

Efficient Detection of Hepatic Steatosis in Ultrasound Images Using Convolutional Neural Networks: A Comparative Study by Fahad M. Alshagathrh (19365478)

“…Problem Statement: This study aims to evaluate deep learning methods for binary classification of hepatic steatosis using ultrasound images. …”

Across the Spectrum In-Depth Review AI-Based Models for Phishing Detection by Shakeel Ahmad (702854)

“…<p dir="ltr">Advancement of the Internet has increased security risks associated with data protection and online shopping. …”