The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)

“…In this context, emerging Deep Reinforcement Learning (DRL) techniques are expected to be one of the main enabling technologies to address the RRAM in future wireless HetNets. …”

Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle by Reza Jafari (3494018)

“…<p dir="ltr">This study presents an innovative solution for simultaneous energy optimization and dynamic yaw control of all-wheel-drive (AWD) electric vehicles (EVs) using deep reinforcement learning (DRL) techniques. To this end, three model-free DRL-based methods, based on deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and TD3 enhanced with curriculum learning (CL TD3), are developed for determining optimal yaw moment control and energy optimization online. …”

A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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

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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…<p>The energy internet (EI) is evolving toward decentralized, data-rich, and time-critical operation, where legacy optimization often fails to meet complexity, scalability, and real-time constraints. Deep reinforcement learning (DRL) offers a data-driven alternative that couples perception with sequential decision-making. …”

Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging by Maricar, Mohammed Farook

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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method by Mohamed Massaoudi (16888710)

“…The meta-model layer exploits deep belief network to generate the final outputs. …”

A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs by Alabd-Aljabar, Ahmed

“…To showcase the performance of such algorithms, we propose two approaches for the task of teeth diagnosis utilizing Orthopantomograms (panoramic radiographs): 1) a direct classification approach; and 2) a hybrid approach that combines a deep learning model with a traditional classifier. …”
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ResultMost traditional machine learning algorithms achieved distinction accuracies of over 99 percent, whereas DeepRaman demonstrated an exceptional accuracy of 100 percent. …”
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A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

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

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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

“…<p dir="ltr">Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different datasets. …”

Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review by Ruba, Sulaiman

“…Once the studies that meet the inclusion criteria were identified, data from these studies were retrieved and were further examined. 17 parameters relevant to TAVI outcomes were carefully identified for assessing the quality of the included studies. …”
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Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection by Ahmad Yaser Alhaddad (7017434)

DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications by Danya A. Saifaldeen (19498705)

“…To address this complexity optimally, we propose a deep reinforcement learning (DRL) approach based on the deep deterministic policy gradient (DDPG) technique. …”

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

“…Data extracted from the included studies were synthesized narratively.…”

Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”