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WQuatNet: Wide range quaternion-based head pose estimation

Journal of King Saud University - Computer and Information Sciences 2025年第3期37卷 1-14页

作者： Algabri, Redhwan Shin, Hyunsoo Abdu, Ahmed Bae, Ji-Hun Lee, Sungon Dept. of Computer Science & Engineering College of AI Convergence Sejong University Seoul 05006 South Korea Research Institute of Engineering and Technology Hanyang University Ansan 15588 South Korea School of Software Northwestern Polytechnical University Xi’an 710072 China Department of Robotics Hanyang University Ansan 15588 South Korea

Head pose estimation (HPE) is a critical task for numerous applications ranging from human-computer interaction, healthcare, and robotics, to surveillance. Most existing methods employ Euler angles as a representation, which often face challenges such as a gimbal lock, especially in full-range rotation scenarios or rotation matrices that require nine parameters. This study introduces WQuatNet, a novel deep learning-based model that leverages the quaternion representation, which uses only four parameters, to avoid this challenge. WQuatNet was designed based on a landmark-free HPE method to predict head poses across the full-range angles of 360∘ from images. Landmark-free methods bypass the need for explicit detection of facial landmarks;instead, they leverage the entire image to estimate the head orientation. The model incorporates a RepVGG-D2se backbone for robust feature extraction and introduces two loss functions tailored for quaternion predictions. Our experimental results on multiple HPE datasets covering both narrow- and full-range angles demonstrate that WQuatNet outperforms the state-of-the-art (SOTA) approaches in terms of accuracy. The performance of the proposed HPE was evaluated using the CMU, AGORA, BIWI, AFLW2000, and 300W-LP datasets. We also perform ablation studies and error analyses to validate the significance of each component of the model. © The Author(s) 2025.

关键词： Deep neural network Full range of rotation Head pose estimation Quaternion

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Video Deblurring by Sharpness Prior Detection and Edge Information

arXiv

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arXiv 2025年

作者： Tian, Yang Brau, Fabio Rossolini, Giulio Buttazzo, Giorgio Meng, Hao The College of Intelligent Systems Science and Engineering Harbin Engineering University Nantong 145 Harbin150001 China DIEE University of Cagliari Via Universit 40 Cagliari09124 Italy Dept. of Excellence in Robotics and AI Sant’Anna School of Advanced Study Via Moruzzi 1 Pisa56124 Italy

Video deblurring is essential task for autonomous driving, facial recognition, and security surveillance. Traditional methods directly estimate motion blur kernels, often introducing artifacts and leading to poor results. Recent approaches utilize the detection of sharp frames within video sequences to enhance deblurring. However, existing datasets rely on fixed number of sharp frames, which may be too restrictive for some applications and may introduce a bias during model training. To address these limitations and enhance domain adaptability, this work first introduces GoPro Random Sharp (GoProRS), a new dataset where the the frequency of sharp frames within the sequence is customizable, allowing more diverse training and testing scenarios. Furthermore, it presents a novel video deblurring model, called SPEINet, that integrates sharp frame features into blurry frame reconstruction through an attention-based encoder-decoder architecture, a lightweight yet robust sharp frame detection and an edge extraction phase. Extensive experimental results demonstrate that SPEINet outperforms state-of-the-art methods across multiple datasets, achieving an average of +3.2% PSNR improvement over recent techniques. Given such promising results, we believe that both the proposed model and dataset pave the way for future advancements in video deblurring based on the detection of sharp frames. © 2025, CC BY-SA.

关键词： Video recording

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Harnessing Medical Imaging Applications: Survey on 3D Deep Learning Models for Image Segmentation 3

Harnessing Medical Imaging Applications: Survey on 3D Deep L...

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3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Nambiar, Rajashree Nanjundegowda, Raghu Dept of Electronics and Communication Bengaluru India Dept of Robotics and Ai Engineering Nitte India Dept of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798331528201

The domain of 3D medical image segmentation has progressed markedly with the incorporation of deep learning methodologies, offering critical instruments for accurate and quick examination of intricate medical pictures. Various research has created 3D convolutional neural networks (CNNs) designed to segment diverse anatomical and pathological features, tackling specific issues such as high dimensionality, class imbalance, and computing requirements. Innovative models such as DeepMedic, which implemented a multiresolution strategy for brain lesion identification, together with other U-Net adaptations, have attained remarkable outcomes in tumor and organ segmentation through the integration of contextual and spatial data. Recent advancements encompass models employing large-kernel (LK) attention modules, transformer-based architectures, and hybrid approaches such as UNETR++ with Efficient Paired Attention, all enhancing accuracy while optimizing computing efficiency. These developments highlight the potential of 3D deep learning for clinical applications;yet, challenges such as restricted data availability, substantial annotation expenses, and generalizability across varied datasets persist as avenues for additional investigation. © 2024 IEEE.

关键词： Convolutional neural networks

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An improved CNN-LSTM deep model for Classification of guideRNA in CRISPR-Casl2 System 2

An improved CNN-LSTM deep model for Classification of guideR...

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2nd IEEE International Conference on Artificial Intelligence in Everything, aiE 2022

作者： Ameen, Zubaida Said Ibrahim, Abdullahi Umar Mubarak, Auwalu Saleh Al-Turjman, Fadi Near East University Research Genter for Ai and IoT Ai and Robotics Institute Artificial Intelligence Dept. Turkey Near East University Biomedical Engineering Nicosia Turkey Ai and Robotics Institute NearEast University Artificial Intelligence Engineering Dept. Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Cyprus

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

Gene editing with CRISPR-Cas12 method has immense applications in diverse organisms from bacteria, and plants to humans especially in treating genetic diseases. GuideRNA and Cas enzyme are the two components required by the Cas12 gene editing method. However, the CRISPR-Cas12 system varies depending on the guideRNA sequence used. Therefore, it is important to develop improved methods for designing guideRNA sequences needed for gene editing. Here, we utilized a combination of convolutional neural networks and long short-term memory a type of recurrent neural network (bi-LSTM) model to classify guideRNA as either active or inactive, and the addition of an embedding layer for encoding guideRNA sequence improved model performance. Accuracy, AUC and F1-score were used to evaluate CNN-LSTM and achieved outstanding performance. CNN-LSTM will help in the design of guideRNA for genes with CRISPR-Cas12 system. © 2022 IEEE.

关键词： Embeddings

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ai in Blockchain Towards Realizing Cyber Security 2

AI in Blockchain Towards Realizing Cyber Security

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2nd IEEE International Conference on Artificial Intelligence in Everything, aiE 2022

作者： Salama, Ramiz Al-Turjman, Fadi Ai and Robotics Institute Research Center for Ai and IoT Near East University Department of Computer Engineering Mersin 10 Nicosia Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin 10 Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Mersin 10 Kyrenia Cyprus

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

Blockchain and artificial intelligence are two technologies that, when combined, have the ability to help each other realize their full potential. Blockchains can guarantee the accessibility and consistent admittance to integrity safeguarded big data indexes from numerous areas, allowing ai systems to learn more effectively and thoroughly. Similarly, artificial intelligence (ai) can be used to offer new consensus processes, and hence new methods of engaging with Blockchains. When it comes to sensitive data, such as corporate, healthcare, and financial data, various security and privacy problems arise that must be properly evaluated. Interaction with Blockchains is vulnerable to data credibility checks, transactional data leakages, data protection rules compliance, on-chain data privacy, and malicious smart contracts. To solve these issues, new security and privacy-preserving technologies are being developed. ai-based blockchain data processing, either based on ai or used to defend ai-based blockchain data processing, is emerging to simplify the integration of these two cutting-edge technologies. © 2022 IEEE.

关键词： Internet of things

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A Review on On Device Privacy and Machine Learning Training 2

A Review on On Device Privacy and Machine Learning Training

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2nd IEEE International Conference on Artificial Intelligence in Everything, aiE 2022

作者： Tonga, Paul Audu Ameen, Zubaida Said Mubarak, Auwalu Saleh Al-Turjman, Fadi Ai and Robotics Institute Near East University Research Center for Ai and IoT Artificial Intelligence Dept Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Cyprus

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

On device machine learning has in recent times attracted growing attention and applications, ranging from advanced OCR and handwriting recognition, smart sleep tracking in Apple iOS, mobile virtual assistants and Image recognition, text translation in android;and more. As a result, there is increasing demand for user privacy and security in machine learning applications. Federated Learning (FL), a new method, allows users to cooperatively train a global model while keeping the data local, thereby resolving the issue of data privacy protection through the encryption mechanism. The server aggregates models until convergence while the clients train their local models. In this procedure, the server employs a reward system to persuade users to provide huge amounts of high-quality data in order to enhance the overall model. This paper explores a few FL techniques that can be applied alongside on-device learning, in order to achieve better privacy and security. © 2022 IEEE.

关键词： Internet of things

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Creation of a Mobile App for engineering Students' Online Lab 2

Creation of a Mobile App for Engineering Students' Online La...

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2nd IEEE International Conference on Artificial Intelligence of Things and Crowdsensing, aioTCs 2022

作者： Salama, Ramiz Al-Turjman, Fadi Ai and Robotics Institute Near East University Research Center for Ai and IoT Department of Computer Engineering Mersin 10 Nicosia Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin 10 Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Mersin 10 Kyrenia Cyprus

ISBN: (纸本)9798350334104

This app helps you access your study materials on your mobile phone. It is an application that allows you to easily communicate with the instructor. Instructors can provide reading materials such as text, images, videos, and links to other sources such as YouTube. It can also be an online video session between instructor and student. Furthermore, this app is a miniature/similar app that adds a laboratory simulation to the university's current online education system (UZEM SYSTEM). This is because the app is aimed at engineering students, and most engineering courses require practicality, so lab internships are required. This allows students to perform laboratory simulations with the help of instructors. The student will need to connect into the app in order to access the contents. Both the teacher and the student will need to select a course from a selection of courses after logging into the site. The chosen course will offer a list of alternatives for learning/teaching techniques, including face-to-face instruction, lab simulations, presentations on a screen, messaging, etc. © 2022 IEEE.

关键词： Students

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Mobile Application System for Online Surveys and Questionnaires

Mobile Application System for Online Surveys and Questionnai...

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2023 International Conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2023

作者： Salama, Ramiz Al-Turjman, Fadi Altrjman, Chadi AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Department of Computer Engineering Mersin 10 Turkey AI and Robotics Institute Near East University Nicosia Artificial Intelligence Engineering Dept Mersin 10 Turkey University of Kyrenia Research Center for AI and IoT Faculty of Engineering Kyrenia Mersin 10 Turkey Waterloo University Canada

ISBN: (纸本)9798350301397

The Covid-19 pandemic, which shook the entire world and altered the dynamics of humanity, resulted in drastic alterations in our life. With the pandemic, human history has understood that the digital world is more important than ever. Existing efforts to digitize pre-pandemic surveys have not entirely replaced face-to-face research. The fundamental issue with online survey platforms can be divided into two categories. It is mostly due to the fact that the particular question types used in practically all research cannot be customized and adjusted using a simple internet program, and certain limited alterations cannot be matched to the research patterns. Second, in addition to the inadequacies of these applications, the online services provided are mainly fee-based programs or applications. The application that is proposed to be established and developed in this context aims to overcome the bottleneck experienced by the end user and to supply the users with high-quality tools that they may use in the global world. © 2023 IEEE.

关键词： Application programs

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Smart Cities Using Artificial Intelligence (ai) and Blockchain in the Internet of Things (IoT) Era 1st

Smart Cities Using Artificial Intelligence (AI) and Blockcha...

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1st International Conference on Smart Environment and Green Technologies, ICSEGT 2024

作者： Al-Turjman, Fadi Salama, Ramiz Sadikoglu, Gunay Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Mersin Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Kyrenia Mersin Turkey Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Mersin Turkey Near East University Nicosia Mersin Turkey

ISBN: (纸本)9783031815638

Around the world, modern cities are changing dramatically in order to install smart infrastructure, provide smart services to residents, improve accessibility for vulnerable populations, and provide a clean, sustainable, and secure environment. Numerous initiatives that address significant issues with urban transportation, health, water management, energy conservation, housing, safety, and accessibility are centered on the adoption of new technologies. To overcome these obstacles and enhance the resourcefulness, sustainability, and security of cities, it is imperative to embrace new and creative technologies, especially in light of the advancements in communication and sensor technology over the past few decades. This article gives a summary of the metropolitan issues that smart urban communities are now experiencing. It investigates how edge ai and blockchain, two recent technological innovations, might revolutionize urban intelligence. It also examines significant research initiatives in these two crucial areas of today’s smart cities, along with a variety of applications for edge ai and blockchain in smart energy and transportation. It discusses numerous uses of blockchain in the context of secure vehicle-to-vehicle trade and communication, along with a range of methods for processing speed detection, counting, and identification to lessen traffic congestion. The purpose of this review article is to set the stage for next research on applying blockchain technology and edge artificial intelligence to smarter city applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Sustainable city

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Future Communication Technology Using Huge Millimeter Waves - An Overview 1

Future Communication Technology Using Huge Millimeter Waves ...

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Chaudhary, Preeti Banda, Latha Near East University Ai and Robotics Institute Research Center for Ai and IoT Department of Computer Engineering Nicosia Turkey Near East University Ai and Robotics Institute Artificial Intelligence Engineering Dept. Nicosia Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Turkey Graphic Era Hill University Computer Science and Engineering Dehradun India Abes Engineering College Ghaziabad India

ISBN: (纸本)9798350338027

Frequency selective surface (FSS) was first created by G. Marconi and C. S. Franklin in 1919 and is known as the "Reflector for Wireless Telegraph and Telephone,"making a significant contribution to our way of life. In terms of the 1960s, it is impossible to overlook the success attained with the employment of regularly selective surfaces in military intelligence units. These structures, which were occasionally applied to land, air, and sea platforms, displayed low pass, high pass, band pass, or band stop characteristics for particular frequencies and served as electromagnetic filters. Many accomplishments have been made, particularly with platforms that are invisible to target detection systems. The geometry and arrangement of the unit cell in these structures, which are successfully used in many fields such as wireless communication systems, radars, and microwaves, allows for the reflection or transmission of the incoming electromagnetic wave. This is made possible by the advancement of technology. High-speed internet connectivity is possible using millimeter wave, a frequency spectrum between 30 GHz and 300 GHz. Its significance has grown in the fields of radio astronomy, radar, remote sensing, and wireless communications. © 2023 IEEE.

关键词： Millimeter waves

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