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.…”

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)

Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting by Abdelkader Baggag (16864140)

“…., its generation, propagation and mitigation, in order to increase operational efficiency and improve livability within smart cities. …”

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

“…Compared to the standard YOLOv11 model, the proposed YOLO-DefXpert attained an improvement of 9.3% and 13.2% in mAP50 and mAP95, an 11.25% increase in frames per second, and a 69.85MB decrease in model size. …”

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). …”

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

“…<p>Automatic food recognition systems have been receiving increasing attention in the research community with the advancements in inductive learning (e.g., classification in computer vision) due to their applicability in the healthcare and hospitality industry. …”

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

“…AI, particularly Convolutional Neural Network (CNN) models, can provide accurate and efficient analysis of ultrasound images, enabling automated detection, improving diagnostic accuracy, and facilitating real-time analysis. Problem Statement: This study aims to evaluate deep learning methods for binary classification of hepatic steatosis using ultrasound images. …”

Blockchain-Based Local Energy Market Enabling P2P Trading: An Australian Collated Case Study on Energy Users, Retailers and Utilities by Liaqat Ali (641438)

“…Moreover, the margins of both energy retailers and distribution utilities are kept unchanged or increased to some extent by the proposed trading model to incorporate them in the LEM framework effectively. …”

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …”

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. …”

Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique by Iqbal Hassan (22155274)

“…<p dir="ltr">The increasing prevalence of non-invasive, portable Electroencephalography (EEG) sensors for neuro-physiological measurements has propelled EEG-based assessments of cognitive load (CL) into the spotlight. …”

Image Steganography: A Review of the Recent Advances by Nandhini Subramanian (16896453)

“…The secret information is hidden in a way that it not visible to the human eyes. Deep learning technology, which has emerged as a powerful tool in various applications including image steganography, has received increased attention recently. …”

Double-Edged Defense: Thwarting Cyber Attacks and Adversarial Machine Learning in IEC 60870-5-104 Smart Grids by Hadir Teryak (17986978)

SPARQ: A Cyber-Resilient Voltage Regulation Using Soft Q-Learning Approach for Autonomous Grid Operations by Mohamed Massaoudi (16888710)

Adaptive PPO With Multi-Armed Bandit Clipping and Meta-Control for Robust Power Grid Operation Under Adversarial Attacks by Mohamed Massaoudi (16888710)

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

“…For a large-sized data set, KPCA’s execution time and occupied storage space will increase drastically and the monitoring performance can also be affected in this case. …”