Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks by Ioannis A. Tsalafoutas (14776939)

“…<h3>Purpose</h3><p dir="ltr">To evaluate image quality (IQ) of for‐processing (raw) and for‐presentation (clinical) radiography images, under different exposure conditions and digital image post‐processing algorithms, using a phantom that enables multiple detection tasks.…”

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…<p dir="ltr">In this article, we present a novel deep learning-based group contribution framework for the targeted design of ionic liquids (ILs). …”

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

MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection by Sui Paul Ang (18460605)

“…<p dir="ltr">Accurate detection of pedestrian lanes is a crucial criterion for vision-impaired people to navigate freely and safely. The current deep learning methods have achieved reasonable accuracy at this task. …”

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

“…This work proposes various machine learning methods, including transfer learning via fine-tuning, transfer learning via feature extraction, ensembles of deep convolutional neural network (CNN) models, and fusion of CNN features, to develop a preliminary dysgraphia diagnosis system based on handwritten images. …”
Get full text
Get full text
Get full text

Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning by Mohamed Elhadary (16329082)

Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques by Arifa Zahir (20748764)

“…Various Deep Learning algorithms, including Convolution Neural Network (CNN), LeNet, and Inception-V3 are implemented to classify the records and extract various patterns. …”

Face Segmentation: A Journey From Classical to Deep Learning Paradigm, Approaches, Trends, and Directions by Khalil Khan (9333883)

“…The approaches presented comprise the seminal works on face segmentation and culminating in SOA approaches of the deep learning architecture. An extensive comparison of the previous approaches is intuitively presented, with a discussion of the potential directions for future research on the topic. …”

Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) by AL SHOUBAKI, HAMZA YOUNIS

“…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …”
Get full text

Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

“…This paper presents a novel deep learning (DL)-based technique that leverages attention mechanisms to improve speech intelligibility through noise suppression. …”

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

“…This work proposes various machine learning methods, including transfer learning via fine-tuning, transfer learning via feature extraction, ensembles of deep convolutional neural network (CNN) models, and fusion of CNN features, to develop a preliminary dysgraphia diagnosis system based on handwritten images. …”

Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework by Tayyabah Hasan (18427887)

“…The framework is basically a merger of a deep learning (DL) agent deployed at the network edge with a quantum memory module (QMM). …”

Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring by Zina Chkirbene (16869987)

“…The core of DRLLVT is its novel algorithm that leverages Deep Reinforcement Learning (DRL) to dynamically adapt to changing environmental conditions, facilitating real-time decisions that consider node capacities, latency, and the overall network dynamics. …”

Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks by Mohammed Almehdhar (22046597)

“…This survey paper offers an in-depth examination of advanced machine learning (ML) and deep learning (DL) approaches employed in developing sophisticated IDS for safeguarding IVNs against potential cyber-attacks. …”

DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor by Maen Takruri (10873368)

Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”

Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

Get full text

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

“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”