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MLFuse: Multi-Scenario Feature Joint Learning for Multi-Modality Image Fusion

IEEE Transactions on Multimedia 2025年

作者： Lei, Jia Li, Jiawei Liu, Jinyuan Wang, Bin Zhou, Shihua Zhang, Qiang Wei, Xiaopeng Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1010 New Zealand Ulster University Intelligent Systems Research Center LondonderryBT52 1SA United Kingdom

Multi-modality image fusion (MMIF) entails synthesizing images with detailed textures and prominent objects. Existing methods tend to use general feature extraction to handle different fusion tasks. However, these methods have difficulty breaking fusion barriers across various modalities owing to the lack of targeted learning routes. In this work, we propose a multi-scenario feature joint learning architecture, MLFuse, that employs the commonalities of multi-modality images to deconstruct the fusion progress. Specifically, we construct a cross-modal knowledge reinforcing network that adopts a multipath calibration strategy to promote information communication between different images. In addition, two professional networks are developed to maintain the salient and textural information of fusion results. The spatial-spectral domain optimizing network can learn the vital relationship of the source image context with the help of spatial attention and spectral attention. The edge-guided learning network utilizes the convolution operations of various receptive fields to capture image texture information. The desired fusion results are obtained by aggregating the outputs from the three networks. Extensive experiments demonstrate the superiority of MLFuse for infrared-visible image fusion and medical image fusion. The excellent results of downstream tasks (i.e., object detection and semantic segmentation) further verify the high-quality fusion performance of our method. The code is publicly available at https://***/jialei-sc/MLFuse. © 1999-2012 IEEE.

关键词： Semantic Segmentation

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Reversible Data Hiding With Secret Encrypted Image Sharing and Adaptive Coding

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IEEE Internet of Things Journal 2025年

作者： Fang, Guangtian Wang, Feng Zhao, Chenbin Qin, Chuan Chang, Ching-Chun Chang, Chin-Chen Fujian University of Technology College of Computer Science and Mathematics Fuzhou350118 China Fujian University of Technology College of Computer Science and Mathematics Key Laboratory of Big Data Mining and Applications Fuzhou350118 China Monash University Faculty of IT Department of Software Systems and Cybersecurity VIC3800 Australia Ministry of Education School of Cyber Science and Engineering Key Laboratory of Aerospace Information Security and Trusted Computing Wuhan430072 China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Feng Chia University Information and Communication Security Research Center Taichuang 40724 Taiwan Feng Chia University Department of Information Engineering and Computer Science Taichung40724 Taiwan

To ensure the security of image information and facilitate efficient management in the cloud, the utilization of reversible data hiding in encrypted images (RDHEI) has emerged as pivotal. However, most existing RDHEI schemes suffer from lower security and limited embedding capacity. To tackle these challenges, we propose a reversible data hiding with secret encrypted image sharing and adaptive coding scheme. Specifically, in the encryption phase, we introduce an improved secret sharing (SS) encryption method based on the chinese remainder theorem for polynomials (CRTP). This method not only improves the security of encrypted images but also vacates a larger room for embedding. In the embedding phase, we introduce an adaptive coding embedding approach using XOR preservation (XORP) and huffman coding, which provides high embedding capacity. Experimental results and security analysis demonstrate that our proposed encryption method achieves optimal values in security indicators for encrypted images, such as information entropy, histograms, NPCR and UACI. The proposed embedding method is superior to some state-of-the-art schemes in terms of embedding capacity. Furthermore, in datasets BOSSBase and BOWS2, the average embedding rates of the proposed embedding approach can reach 2.1745 bpp and 2.0656 bpp, respectively. © 2025 IEEE.

关键词： adaptive coding chinese remainder theorem for polynomials encrypted images Reversible data hiding secret sharing

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Dynamic Pricing based Near-Optimal Resource Allocation for Elastic Edge Offloading

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IEEE Transactions on Mobile Computing 2025年

作者： Xia, Yun Xue, Hai Zhang, Di Mumtaz, Shahid Xu, Xiaolong Rodrigues, Joel J. P. C. University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Zhengzhou University School of Electrical and Information Engineering Henan International Joint Laboratory of Intelligent Health Information System National Telemedicine Center National Engineering Laboratory for Internet Medical Systems and Applications Zhengzhou450001 China Nottingham Trent University Department of Engineering NottinghamNG1 4FQ United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of Nanjing University of Information Science and Technology School of Software Nanjing210044 China Amazonas State University Manaus Brazil

In mobile edge computing (MEC), task offloading can significantly reduce task execution latency and energy consumption of end user (EU). However, edge server (ES) resources are limited, necessitating efficient allocation to ensure the sustainable and healthy development for MEC system. In this paper, we propose a dynamic pricing mechanism based near-optimal resource allocation for elastic edge offloading. First, we construct a resource pricing model and accordingly develop the utility functions for both EU and ES, the optimal pricing model parameters are derived by optimizing the utility functions. In the meantime, our theoretical analysis reveals that the EU's utility function reaches a local maximum within the search range, but exhibits barely growth with increased resource allocation beyond this point. To this end, we further propose the Dynamic Inertia and Speed-Constrained particle swarm optimization (DISC-PSO) algorithm, which efficiently identifies the near-optimal resource allocation. Comprehensive simulation results validate the effectiveness of DISC-PSO algorithm, demonstrating that it significantly outperforms existing schemes by reducing the average number of iterations to reach a near-optimal solution by 86.88%, increasing the EU utility function value by 0.13%, and decreasing the variance of results by 96.78%. © 2025 IEEE. All rights reserved.

关键词： Mobile edge computing

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Towards Connecting Discrete Mathematics and software engineering

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Tsinghua Science and Technology 2020年第3期25卷 325-335页

作者： Tun Li Wanwei Liu Juan Chen Xiaoguang Mao Xinjun Mao the School of Computer National University of Defense Technology and are also with Laboratory of Software Engineering for Complex Systems

To enhance training in software development,we argue that students of software engineering should be exposed to software development activities early in the *** entails meeting the challenge of engaging students in software development before they take the software engineering *** this paper,we propose a method to connect courses in the software engineering curriculum by setting comprehensive development projects to students in prerequisite courses for software *** the Discrete Mathematics(DM)course as an example,we describe the implementation of the proposed method and teaching practices using several practical and comprehensive projects derived from topics in discrete *** descriptions of the sample projects,their application,and training results are *** and lessons learned from applying these practices show that it is a promising way to connect courses in the software engineering curriculum.

关键词： Discrete Mathematics(DM) software engineering proof checker database management system symbolic execution engine

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Correction to: A comprehensive performance evaluation of container migration strategies

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Computing 2025年第4期107卷 1-2页

作者： Feitosa, Leonel Barbosa, Vandirleya Sabino, Arthur Lima, Luiz Nelson Fé, Iure Silva, Luis Guilherme Callou, Gustavo Carvalho, Juliana Leão, Erico Nguyen, Tuan Anh Rego, Paulo Silva, Francisco Airton Laboratory of Applied Research to Distributed Systems (PASID) Federal University of Piauí (UFPI) Picos Brazil Department of Computing Federal Rural University of Pernambuco (UFRPE) Recife Brazil Department of Software Engineering Faculty of Information Technology University of Industry and Trade (HUIT) Ho Chi Minh City Vietnam Department of Computer Science Federal University of Ceará (UFC) Fortaleza Brazil

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The role of GPT in promoting inclusive higher education for people with various learning disabilities: a review

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PeerJ computer Science 2025年 11卷 e2400-e2400页

作者： Gadekallu, Thippa Reddy Yenduri, Gokul Kaluri, Rajesh Rajput, Dharmendra Singh Lakshmanna, Kuruva Fang, Kai Chen, Junxin Wang, Wei Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon School of Computer Science Engineering and Information Systems Vellore Institute of Technology University Tamil Nadu India Zhongda Group Jiaxing China College of Information Science and Engineering Jiaxing University Jiaxing China Division of Research and Development Lovely Professional University Phagwara India School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati India School of Mathematics and Computer Science Zhejiang Agricultural and Forestry University Hangzhou China School of Software Dalian University of Technology Dalian China Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen China School of Medical Technology Beijing Institute of Technology Beijing China

The generative pre-trained transformer (GPT) is a notable breakthrough in the field of artificial intelligence, as it empowers machines to effectively comprehend and engage in interactions with humans. The GPT exhibits the capacity to enhance inclusivity and accessibility for students with learning disabilities in the context of higher education, hence potentially facilitating substantial advancements in the field. GPT can provide personalized and diverse solutions that successfully cater to the distinct requirements of students with learning disabilities. This motivated us to conduct an extensive review to assess the effectiveness of GPT in enhancing accessibility and inclusivity in higher education for students with learning disabilities. This review offers a comprehensive analysis of the GPT and its significance for enhancing inclusivity in the field of higher education. In this research, we also examined the possible challenges and constraints associated with the integration of GPT into inclusive higher education, along with potential solutions. Overall, this review is intended for educators, students with and without learning disabilities, policymakers, higher education institutes, researchers, and educational technology developers. This review aims to provide a comprehensive understanding of GPT in promoting inclusive higher education for people with various learning disabilities, its impacts on inclusive higher education, emerging challenges, and potential solutions. Copyright 2025 Gadekallu et al.

关键词： Contrastive Learning

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On the round trip path testing strategy

On the round trip path testing strategy

引用

2010 IEEE 21st International Symposium on software Reliability engineering, ISSRE 2010

作者： Khalil, May Labiche, Yvan Carleton University Dept. Systems and Computer Engineering Software Quality Engineering Laboratory Ottawa ON Canada

ISBN: (纸本)9780769542553

A number of techniques have been proposed for state-based testing. One well-known technique (criterion) is to traverse the graph representing the state machine and generate a so-called transition tree, in an attempt to exercise round trip paths, i.e., paths that start and end in the same state without any other repeating state. Several hypotheses are made when one uses this criterion: exercising paths in the tree, which do not always trigger complete round trip paths, is equivalent to covering round-trip paths;different traversal algorithms are equivalent. In this paper we investigate whether these assumptions hold in practice, and if they do not, we investigate their consequences. Results also lead us to propose a new transition tree construction algorithm that results in higher efficiency and lower cost. © 2010 IEEE.

关键词： Forestry

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ForkXplorer:an approach of fork summary generation

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Frontiers of computer Science 2022年第2期16卷 1-15页

作者： Zhang ZHANG Xinjun MAO Chao ZHANG Yao LU Key Laboratory of Software Engineering for Complex Systems College of ComputerNational University of Defense TechnologyChangsha 410073China

Pull-based development has become an important paradigm for distributed software *** this model,each developer independently works on a copied repository(i.e.,a fork)from the central *** is essential for developers to maintain awareness of the state of other forks to improve collaboration *** this paper,we propose a method to automatically generate a summary of a *** first use the random forest method to generate the label of a fork,i.e.,feature implementation or a bug *** on the information of the fork-related commits,we then use the TextRank algorithm to generate detailed activity information of the ***,we apply a set of rules to integrate all related information to construct a complete fork *** validate the effectiveness of our method,we conduct 30 groups of manual experiment and 77 groups of case studies on *** propose Fea_(avg)to evaluate the performance of Fea_(avg)the generated fork summary,considering the content accuracy,content integrity,sentence fluency,and label extraction *** results show that the average of of the fork summary generated by this method is *** than 63%of project maintainers and the contributors believe that the fork summary can improve development efficiency.

关键词： open source software pull-based development fork summary distributed cooperative development

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Efficient and Trustworthy Block Propagation for Blockchain-enabled Mobile Embodied AI Networks: A Graph Resfusion Approach

arXiv

引用

arXiv 2025年

作者： Kang, Jiawen Liao, Jiana Gao, Runquan Wen, Jinbo Huang, Huawei Zhang, Maomao Yi, Changyan Zhang, Tao Niyato, Dusit Zheng, Zibin Anhui Engineering Research Center for Agricultural Product Quality Safety Digital Intelligence Fuyang Normal University Fuyang236037 China School of Automation Guangdong University of Technology Guangzhou510006 China School of Software Engineering Sun Yat-Sen University Zhuhai519082 China School of Intelligent Systems Engineering Sun Yat-Sen University Shenzhen518107 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Cyberspace Science and Technology Beijing Jiaotong University Beijing100044 China College of Computing and Data Science Nanyang Technological University Singapore

By synergistically integrating mobile networks and embodied artificial intelligence (AI), Mobile Embodied AI Networks (MEANETs) represent an advanced paradigm that facilitates autonomous, context-aware, and interactive behaviors within dynamic environments. Nevertheless, the rapid development of MEANETs is accompanied by challenges in trustworthiness and operational efficiency. Fortunately, blockchain technology, with its decentralized and immutable characteristics, offers promising solutions for MEANETs. However, existing block propagation mechanisms suffer from challenges such as low propagation efficiency and weak security for block propagation, which results in delayed transmission of vehicular messages or vulnerability to malicious tampering, potentially causing severe traffic accidents in blockchain-enabled MEANETs. Moreover, current block propagation strategies cannot effectively adapt to real-time changes of dynamic topology in MEANETs. Therefore, in this paper, we propose a graph Resfusion model-based trustworthy block propagation optimization framework for consortium blockchain-enabled MEANETs. Specifically, we propose an innovative trust calculation mechanism based on the trust cloud model, which comprehensively accounts for randomness and fuzziness in the miner trust evaluation. Furthermore, by leveraging the strengths of graph neural networks and diffusion models, we develop a graph Resfusion model to effectively and adaptively generate the optimal block propagation trajectory. Simulation results demonstrate that the proposed model outperforms other routing mechanisms in terms of block propagation efficiency and trustworthiness. Additionally, the results highlight its strong adaptability to dynamic environments, making it particularly suitable for rapidly changing MEANETs. Copyright © 2025, The Authors. All rights reserved.

关键词： Graph neural networks

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Diff-Reg v2: Diffusion-Based Matching Matrix Estimation for Image Matching and 3D Registration

arXiv

引用

arXiv 2025年

作者： Wu, Qianliang Jiang, Haobo Ding, Yaqing Luo, Lei Xie, Jin Yang, Jian PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China School of Computer Science and Engineering Nanjing University of Science and Technology China Nanyang Technological University Singapore Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic State Key Laboratory for Novel Software Technology Nanjing University Nanjing China School of Intelligence Science and Technology Nanjing University Suzhou China

Establishing reliable correspondences is crucial for all registration tasks, including 2D image registration, 3D point cloud registration, and 2D-3D image-to-point cloud registration. However, these tasks are often complicated by challenges such as scale inconsistencies, symmetry, and large deformations, which can lead to ambiguous matches. Previous feature-based and correspondence-based methods typically rely on geometric or semantic features to generate or polish initial potential correspondences. Some methods typically leverage specific geometric priors, such as topological preservation, to devise diverse and innovative strategies tailored to a given enhancement goal, which cannot be exhaustively enumerated. Additionally, many previous approaches rely on a single-step prediction head, which can struggle with local minima in complex matching scenarios. To address these challenges, we introduce an innovative paradigm that leverages a diffusion model in matrix space for robust matching matrix estimation. Our model treats correspondence estimation as a denoising diffusion process in the matching matrix space, gradually refining the intermediate matching matrix to the optimal one. Specifically, we apply the diffusion model in the doubly stochastic matrix space for 3D-3D and 2D-3D registration tasks. In the 2D image registration task, we deploy the diffusion model in a matrix sub-space, where dual-softmax projection regularization is applied. For all three registration tasks, we provide adaptive matching matrix embedding implementations tailored to the specific characteristics of each task while maintaining a consistent"match-to-warp" encoding pattern. Furthermore, we adopt a lightweight design for the denoising module. In inference, once points or image features are extracted and fixed, this module performs multi-step denoising predictions through reverse sampling. Evaluations on both 2D and 3D registration tasks demonstrate the effectiveness of our approach. Copyrigh

关键词： Stochastic systems

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