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Arbitrary style transfer system with split-and-transform scheme

Multimedia Tools and Applications 2024年第23期83卷 62497-62517页

作者： Tu, Ching-Ting Lin, Hwei Jen Tsai, Yihjia Lin, Zi-Jun Department of Applied Mathematics National Chung Hsing University Taichung Taiwan Department of Computer Science and Information Engineering Tamkang University New Taipei Taiwan

For the subject of arbitrary image style transfer, there have been some proposed architectures that directly compute the transformation matrix of the whitening and coloring transformation (WCT) to obtain more satisfactory transformation results. However, calculating the transformation matrix of WCT is time-consuming. Li et al. trained a linear transformation module to generate a WCT transformation matrix for any pair of images, i.e., content image and style image, to avoid complex calculations and improves time efficiency. In this work, we introduce a flexible arbitrary image style transfer framework based on the LST, which uses deep neural networks to train a linear transformation matrix as the standard matrix for WCT. For the first part, inverse relationship between the Whitening matrix and the Coloring matrix w.r.t. the same image is enforced during the training of the linear transformation matrix, so that the resulting matrix will be more accurate and closer to the standard matrix of WCT. For the second part, a split-and-transform scheme is proposed. Unlike LST, which transforms the block of feature maps as a whole, the split-and-transform scheme divides the feature block into several smaller blocks and transforms them individually, so that the transformation is more localized, and the more the number of divided blocks, the more localized. In addition, the proposed split-and-transform scheme allows users to determine the number of divided blocks to flexibly control the locality of the transformations. Experimental results demonstrate the effectiveness and flexibility of the proposed framework by the high-quality stylized images and adjustable balance between globality and locality of transformations. The use of the split-and-transform scheme can reduce the computational time while preserving or even improving the stylization results. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Linear transformations

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Problems in Video Conferencing-Mediated Teaching: Experiences of Three User Roles of a University in Bangladesh

Problems in Video Conferencing-Mediated Teaching: Experience...

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2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Mansoor, Nafees Rozario, Anatte Kibria, Muhammad Golam Khalid, Md Saifuddin University of Liberal Arts Department of Computer Science and Engineering Bangladesh Department of Applied Mathematics and Computer Science Kongens Lyngby Denmark

ISBN: (纸本)9798350350289

Video-conferencing systems (VCS) became a defacto tool for online and hybrid teaching during COVID-19 and the gradual return to physical classrooms. As part of the EdViCon Erasmus+ project, towards defining the scenarios for improving teaching with additional portable tools by university teachers, this study reports users' problems in the context of the University of Liberal Arts Bangladesh (ULAB). Classroom observations, problem-tree analysis, interviews, and focus-group discussions with academics, e-learning and IT consultants, and students provide different perspectives on the central problems, underlying causes, and the effects of VCS use during live teaching sessions. While teachers emphasized the lack of resources and technical barriers, students' problem statement focused on the reduced quality of interactions due to the differences between VCS-mediated and physical classrooms, and the IT & e-learning professionals emphasized technological issues (audio, tone, lack of facial expression etc.), lack of collaboration, and differences in expectations among participants. The central contribution of this paper is three diagrams showing problem tree analysis from the perspectives of the three roles. Each of the causes, effects, and problem statements will be considered as point-of-view statements for generating ideas for supporting hardware and software tools and training on technology and pedagogy, © 2024 IEEE.

关键词： Students

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Predicting Student Behavior Using a Neutrosophic Deep Learning Model

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Neutrosophic Sets and Systems 2025年 76卷 288-310页

作者： Shitaya, Ahmed Mohamed Wahed, Mohamed El Syed Abd El Khalek, Saied Helemy Ismail, Amr Shams, Mahmoud Y. Salama, A.A. Department of Mathematics and Computer Science Faculty of Science Port Said University Egypt Department of Computer Science Faculty of computer and information sciences Suez Canal University Egypt Department. of Communication and Computer Engineering Air Defense University Egypt Department of Cybersecurity College of Engineering and Information Technology Buraydah Private Colleges Buraydah51418 Saudi Arabia Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh33516 Egypt

We developed an information system using an object-oriented programming language and a distributed database (DDB) consisting of multiple interconnected databases across a computer network, managed by a distributed database management system (DDBMS) for easy access. An intelligent system was designed to assess the difficulty level of preliminary exams and select top-performing advanced students using a Neutrosophic Deep Learning Model. The dataset was randomly split into training (80%) and testing (20%) sets, and the model, trained with the Adam optimizer at a 0.001 learning rate over 50 epochs, incorporated early stopping based on validation loss. This system, implemented at a traditional Egyptian university, achieved a 95% accuracy in predicting student dropout. Student behavior, influenced by personal, environmental, and academic factors, is often evaluated subjectively, leading to inconsistent results. Traditional machine learning approaches struggle with the inherent uncertainty in behavioral data. To address this, we combined neutrosophic theory—a mathematical framework that accounts for truth, falsity, and indeterminacy—with deep learning, which excels at learning complex data relationships, to predict student outcomes such as dropout rates. Evaluating the model on student data, including attendance and grades, showed superior accuracy, achieving a determination coefficient of 0.95, demonstrating the approach's potential for identifying at-risk students and enabling targeted interventions. © 2025, University of New Mexico. All rights reserved.

关键词： Contrastive Learning

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A Neutrosophic Study for the Transmission of Infection with Pathogenic Fungi from Males of Olive Fly Insects to Their Females

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Neutrosophic Sets and Systems 2024年 64卷 38-45页

作者： Alhabib, Amani Alhabib, Rafif Khalid, Huda E. Salama, A.A. Faculty of Agricultural Engineering Albaath University Homs Syria Department of Mathematics Faculty of Science Hama University Hama Syria Telafer University Telafer Iraq Department of Mathematics and Computer Science Faculty of Science Port Said University Port Said Egypt

This paper presents the study of the effectiveness of horizontal transfer of local isolates of the pathogenic fungus Beauveria bassiana (Balsamo) on adults of olive fruit fly Bactrocera oleae (Rossi) at a concentration of 106 spores/ml in laboratory conditions (this work was carried out in specialized scientific laboratories). In addition, it is not possible to reach the desired results in such experiments effectively when the data and observations of the study are not clear and accurate. For this reason, in this paper, experimental data will be presented with inaccurate or uncertain observations using neutrosophic statistics. The purpose is to know the success of males contaminated with pathogenic isolates in the transmission of infection to females. In laboratory conditions through a neutrosophic reading of the study data. This proposed presentation provides greater accuracy, flexibility, and applicability than the classic experimental design in the case of uncertainty. © (2023), (University of New Mexico). All Rights Reserved.

关键词： Transmissions

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Reliability modelling of a grid integration system with dual operational and quintuple critical systems

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Life Cycle Reliability and Safety engineering 2025年第2期14卷 141-150页

作者： Kharola, Shristi Shivani Chachra, Aayushi Ram, Mangey Department of Mathematics Graphic Era (Deemed to be University) Dehradun India Department of Mathematics Computer Science and Engineering Graphic Era (Deemed to be University) Dehradun India

The current crisis of environmental pollution and depleting resources has led to a rise in the demand for renewable energy sources and systems functioning on such resources. However, their variable and unpredictable nature has challenges on its own. A grid integration system can help in maintaining and intensifying system stability and reliability by managing flexible renewable energy for future purposes. This work is based on a generic model of a grid integration system that takes into account all of its important components, both critical and non-critical. By classifying the components according to their failure properties, an analytical reliability model has been used to assess the reliability features of the whole system. The complete system has been categorized into two major systems, operational system and critical system. The system’s reliability characteristics including availability, mean-time-to-failure and sensitivity have been calculated to observe the performance of the complete system and its failure possibilities. Overall, an attempt has been made to study the significance of each component using past literature and a mathematical model based on the Markov Process property. © The Author(s), under exclusive licence to Society for Reliability and Safety (SRESA) 2024.

关键词： Availability Grid system Mean-time-to-failure Reliability Renewable energy system Sensitivity analysis

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GRA: Graph Representation Alignment for Semi-Supervised Action Recognition

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IEEE Transactions on Neural Networks and Learning Systems 2024年第9期35卷 11896-11905页

作者： Huang, Kuan-Hung Huang, Yao-Bang Lin, Yong-Xiang Hua, Kai-Lung Tanveer, M. Lu, Xuequan Razzak, Imran National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei10607 Taiwan Indian Institute of Technology Indore Department of Mathematics Indore Simrol453552 India La Trobe University Department of Computer Science and IT MelbourneVIC3086 Australia University of New South Wales School of Computer Science and Engineering SydneyNSW2052 Australia

Graph convolutional networks (GCNs) have emerged as a powerful tool for action recognition, leveraging skeletal graphs to encapsulate human motion. Despite their efficacy, a significant challenge remains the dependency on huge labeled datasets. Acquiring such datasets is often prohibitive, and the frequent occurrence of incomplete skeleton data, typified by absent joints and frames, complicates the testing phase. To tackle these issues, we present graph representation alignment (GRA), a novel approach with two main contributions: 1) a self-training (ST) paradigm that substantially reduces the need for labeled data by generating high-quality pseudo-labels, ensuring model stability even with minimal labeled inputs and 2) a representation alignment (RA) technique that utilizes consistency regularization to effectively reduce the impact of missing data components. Our extensive evaluations on the NTU RGB+D and Northwestern-UCLA (N-UCLA) benchmarks demonstrate that GRA not only improves GCN performance in data-constrained environments but also retains impressive performance in the face of data incompleteness. © 2012 IEEE.

关键词： Alignment

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Light Weighted YOLO Vehicle Tracker for Toll Gate Using Centroid Algorithm 3rd

Light Weighted YOLO Vehicle Tracker for Toll Gate Using Cen...

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3rd International Conference on Emerging Electronics and Automation, E2A 2023

作者： Singh, Pankaj Pratap Prasad, Shitala Kalita, Gyanjyoti Das, Jahnu Mahanta, Pallab Jyoti Department of Computer Science and Engineering CIT Kokrajhar Assam India School of Mathematics and Computer Science IIT Goa Goa India

ISBN: (纸本)9789819730896

This paper focuses on vehicle detection at highway toll gates. The study involves the detection of vehicles within a custom dataset, which comprises four vehicle classes: car, truck, bus, and motorcycle. The YOLOv4 model is utilized for training and is complemented by the implementation of the Centroid tracking algorithm. In the proposed vehicle track dataset, each class comprises 1500 annotated images for training and 300 images in the testset. These images are sourced from the Google Open Images V6 dataset, and the OIDv4 toolkit is employed to scrape dataset images. The primary objective of this study is to train a vehicle detection model and evaluate the effectiveness of various tracking algorithms, with a specific focus on the centroid tracker for real-time application at the toll gates. Importantly, this model is designed to operate efficiently on conventional and cost-effective GPUs and demonstrates a commendable level of precision. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image annotation

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A Unified Multi-Domain Face Normalization Framework for Cross-domain Prototype Learning and Heterogeneous Face Recognition

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5282-5295页

作者： Pang, Meng Zhang, Wenjun Lu, Yang Cheung, Yiu-Ming Zhou, Nanrun Nanchang University School of Mathematics and Computer Sciences China Xiamen University Department of Computer Science and Technology School of Informatics China Hong Kong Baptist University Department of Computer Science Hong Kong Hong Kong Shanghai University of Engineering Science School of Electronic and Electrical Engineering China

Face normalization is a critical technique for improving the robustness and generalizability of face recognition systems by reducing intra-personal variations arising from expressions, poses, occlusions, illuminations, and domain shifts. Existing normalization methods, however, often lack the flexibility to handle multi-factorial variations and exhibit limited cross-domain adaptability. To address these challenges, we propose a Unified Multi-Domain Face Normalization Network (UMFN), which is designed to process facial images with diverse variations from various domains and reconstruct frontal, neutralized facial prototypes in the target domain. As an unsupervised domain adaptation model, the UMFN facilitates concurrent training across multiple cross-domain datasets and demonstrates robust prototype reconstruction capabilities. Notably, the UMFN functions as a joint prototype and feature learning framework, extracting domain-agnostic identity features through a decoupling mapping network and adversarial training with a feature domain classifier. Furthermore, we design an efficient Heterogeneous Face Recognition (HFR) network that integrates these domain-agnostic features and the identity-discriminative features extracted from normalized prototypes, enhanced by contrastive learning to improve identity recognition accuracy. Empirical evaluation on multiple cross-domain benchmark datasets validate the effectiveness of the UMFN for face normalization and the superiority of the HFR network for heterogeneous face recognition. © 2005-2012 IEEE.

关键词： Adversarial machine learning

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Fault-tolerant properties of scale-free linear protocols for synchronization of homogeneous multi-agent systems

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IEEE Transactions on Automatic Control 2025年第6期70卷 4194-4201页

作者： Stoorvogel, Anton A. Saberi, Ali Liu, Zhenwei University of Twente Department of Electrical Engineering Mathematics and Computer Science P.O. Box 217 Enschede Netherlands Washington State University School of Electrical Engineering and Computer Science PullmanWA99164 United States Northeastern University College of Information Science and Engineering Shenyang110819 China

Originally, protocols were designed for multi-agent systems (MAS) using information about the network which might not be available. Recently, there has been a focus on scale-free synchronization where the protocol is designed without any prior information about the network. As long as the network contains a directed spanning tree, a scale-free protocol guarantees that the network achieves synchronization. If there is no directed spanning tree then synchronization cannot be achieved. But what happens when these scale-free protocols are applied to such a network where the directed spanning tree no longer exists? This paper establishes that the network decomposes into a number of basic bicomponents which achieves synchronization among all nodes in this basic bicomponent. On the other hand, nodes which are not part of any basic bicomponent converge to a weighted average of the synchronized trajectories of the basic bicomponents. The weights are independent of the initial conditions and are independent of the designed protocol. © 1963-2012 IEEE.

关键词： Synchronization

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A Study on the Transmission Dynamics of the Omicron Variant of COVID-19 Using Nonlinear Mathematical Models

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computer Modeling in engineering & sciences 2024年第6期139卷 2265-2287页

作者： S.Dickson S.Padmasekaran Pushpendra Kumar Kottakkaran Sooppy Nisar Hamidreza Marasi Department of Mathematics Periyar UniversitySalemTamilnadu636011India Faculty of Engineering and Natural Sciences Istanbul Okan UniversityIstanbulTurkey Department of Mathematics College of Science and Humanities in AlkharjPrince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Applied Mathematics Faculty of MathematicsStatistics and Computer ScienceUniversity of TabrizTabrizIran

This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models,considering the delay in converting susceptible individuals into infected *** significant delays eventually resulted in the pandemic’s *** ensure the safety of the host population,this concept integrates quarantine and the COVID-19 *** investigate the stability of the proposed *** fundamental reproduction number influences stability *** to our findings,asymptomatic cases considerably impact the prevalence of Omicron infection in the *** real data of the Omicron variant from Chennai,Tamil Nadu,India,is used to validate the outputs.

关键词： Omicron local stability reproduction number steady states global stability

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