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24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023

作者： Zhou, XingZhi Liu, Xiang Wen, YiMin Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9783031482311

To handle data stream classification with concept drifts, recent studies have shown that a continuously evolving network structure can achieve better performance. However, firstly, they only change one hidden node at a time, which is not enough to alleviate underfitting or overfitting of network model, leading to model’s inability to fit data well. Secondly, during the growth process of the network, they did not consider reducing hidden layers, which would affect the learning ability of deep neural network models. To overcome these shortcomings, an adaptive neural network structure (ANSN) is proposed to handle data stream classification with concept drifts. ANSN has a completely open structure, its network structure, depth, and width can evolve automatically in online mode. The experimental results on ten popular data stream datasets show that the proposed ANSN outperforms the comparison methods. The codes of the proposed algorithm is available on https://***/ymw12345/***. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Deep neural networks

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Dynamic Color Transform Networks for Wheat Head Detection

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Plant Phenomics 2022年第1期4卷 395-408页

作者： Chengxin Liu Kewei Wang Hao Lu Zhiguo Cao Key Laboratory of Image Processing and Intelligent Control Ministry of EducationSchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhanChina

Wheat head detection can measure wheat traits such as head density and head *** wheat breeding largely relies on manual observation to detect wheat heads,yielding a tedious and inefficient *** emergence of affordable camera platforms provides opportunities for deploying computer vision(CV)algorithms in wheat head detection,enabling automated measurements of wheat *** wheat head detection,however,is challenging due to the variability of observation circumstances and the uncertainty of wheat head *** this work,we propose a simple but effective idea—dynamic color transform(DCT)—for accurate wheat head detection.

关键词： Wheat breeding wheat

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Single-Component Color-Tunable Smart Organic Emitters with Simultaneous Multistage Stimuli-Responsiveness and Multimode Emissions

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Research 2024年第2期2023卷 719-728页

作者： Yu Yan Chengfang Liu Jianzhong Fan Yusheng Li Huanling Liu Qian Wang Xiangchun Lil Junfeng Li Wen-Yong Lai State Key Laboratory of Organic Electronics and Information Displays(SKLOEID) Institute of Advanced Materials(IAM)School of Chemistry and Life SciencesNanjing University of Posts&Telecommunications9 Wenyuan RoadNanjng 210023China Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and ElectronicsShandong Normal UniversityJinan 250358China

Achieving color-tunable emission in single-component organic emitters with multistage stimuli-responsiveness is of vital significance for intelligent optoelectronic applications,but remains enormously ***,we present an unprecedented example of a color-tunable single-component smart organic emitter(DDOP)that simultaneously exhibits multistage stimuli-responsiveness and multimode *** based on a highly twisted amide-bridged donor-tcceptor-donor structure has been found to facilitate intersystem crossing,form multimode emissions,and generate multiple emissive species with multistage *** pristine crystalline powders exhibit abnormal excitation-dependent emissions from a monomer-dominated blue emission centered at 470 nm to a dimer-dominated yellow emission centered at 550 nm through decreasing the ultraviolet(UV)excitation wavelengths,whereas DDOP single crystals show a wide emission band with a main emission peak at 585 nm when excited at different *** emission behaviors of pristine crystalline powders and single crystals are different,demonstrating emission features that are closely related to the aggregation *** work has developed color-tunable single-component organic emitters with simultaneous multistage stimuli-responsiveness and multimode emissions,which is vital for expanding intelligent optoelectronic applications,including multilevel information encryption,multicolor emissive patterns,and visual monitoring of UV wavelengths.

关键词： donor excitation Smart

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A Survey on Negative Transfer

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 305-329页

作者： Wen Zhang Lingfei Deng Lei Zhang Dongrui Wu the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China IEEE the School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China

Transfer learning(TL)utilizes data or knowledge from one or more source domains to facilitate learning in a target *** is particularly useful when the target domain has very few or no labeled data,due to annotation expense,privacy concerns,***,the effectiveness of TL is not always *** transfer(NT),i.e.,leveraging source domain data/knowledge undesirably reduces learning performance in the target domain,and has been a long-standing and challenging problem in *** approaches have been proposed in the literature to address this ***,there does not exist a systematic *** paper fills this gap,by first introducing the definition of NT and its causes,and reviewing over fifty representative approaches for overcoming NT,which fall into three categories:domain similarity estimation,safe transfer,and NT *** areas,including computer vision,bioinformatics,natural language processing,recommender systems,and robotics,that use NT mitigation strategies to facilitate positive transfers,are also ***,we give guidelines on NT task construction and baseline algorithms,benchmark existing TL and NT mitigation approaches on three NT-specific datasets,and point out challenges and future research *** ensure reproducibility,our code is publicized at https://***/chamwen/NT-Benchmark.

关键词： Domain adaptation domain similarity negative transfer positive transfer transfer learning

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Dynamic Student Classification with Forgetting Mechanisms on Memory Networks for Knowledge Tracing 5

Dynamic Student Classification with Forgetting Mechanisms on...

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5th International Conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2024

作者： Huang, Guimin Qin, Xiangqian School of Computer Science and Information Security Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin China

ISBN: (纸本)9798350368284

Knowledge Tracing (KT), a technique for modeling students' knowledge levels and predicting their future question-answering performance based on their historical answer data, is one of the key research areas to strengthen the ability of personalized education. In recent years, memory networks have received more and more attention and application in the field of KT, however, the current KT model based on memory networks ignores the effect of students' learning sequence on the level of forgetting, and fails to model the forgetting behavior of students in the process of learning by using the characteristics of time intervals in the interaction data. Therefore, in this paper, we propose a dynamic student classification with forgetting mechanisms on memory networks model (DSCFMN), which enhance the existing model by dynamically classifying students similar to their learning abilities at specified time intervals, incorporating forgetting factors and introducing a weight decay strategy. Experiments show that our model performs well on online education datasets, and the proposed model achieves better prediction results than existing knowledge tracking methods. © 2024 IEEE.

关键词： Contrastive Learning

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5th International Conference on Big Data and Artificial Intelligence and Software Engineering, ICBASE 2024

作者： Zhou, Ya Chen, Chen Huang, Guimin Guilin University of Electronic Technology School of Computer Science and Information Security Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin China

ISBN: (纸本)9798331506612

In the research methods of sentence similarity, sentence similarity is often calculated from the semantic aspect, while the influence of syntactic structure is ignored. We propose an enhanced knowledge language representation model (ExtKBRCNN) based on CNN and Bi-GRU, which effectively uses the fine-grained word relations in the knowledge base to evaluate semantic similarity and models the relationship between knowledge structure and text structure. In order to make full use of the syntactic information of the sentence, we also propose a dependency tree kernel-based method (Dep-SIF), which combines syntactic information and semantic features to evaluate syntactic similarity. Finally, we propose a comprehensive model that integrates semantic and syntactic information to comprehensively evaluate sentence similarity. Experimental results show that the accuracy of the model on the MRPC dataset is 77.63% and the F1 value is 83.90%. © 2024 IEEE.

关键词： Semantics

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SiamAHG: adaptive hierarchical graph attention for lightweight siamese tracking

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Journal of King Saud University - Computer and Information Sciences 2025年第4期37卷 1-12页

作者： Li, Na Fan, Yaofu Chen, Xuhao Liu, Xinyu He, Jinglu School of Communications and Information Engineering Xi’an University of Posts and Telecommunications Xi’an 710121 China Xi’an Key Laboratory of Image Processing Technology and Applications for Public Security Xi’an 710121 China International Joint Research Center for Wireless Communication and Information Processing Technology of Shaanxi Province Xi’an 710121 China

In order to balance the tracking performance and inference speed, a lightweight Siamese-based tracker named SiamAHG is proposed in this paper. It employs the lightweight network ShuffleNet V2 for feature extraction and a novel adaptive hierarchical graph attention for feature fusion. Specifically, the feature fusion sub-network consists of an adaptive feature map refinement module (AFMRM) and a hierarchical graph attention module (HGAM). AFMRM refines feature maps of different stages and strengthens the model expression by combining multiple convolutional kernels dynamically based upon diverse attentions. HGAM realizes node-level information interaction of the same stage between the template and search branches, and integrates the features of different stages to get complementary information for tracking. Experiments on LaSOT, OTB100, GOT-10k, and UAV123 validate the effectiveness and efficiency of our proposed tracker. It has significant advantages in model complexity and inference speed, while achieving competitive results with state-of-the-art trackers. © The Author(s) 2025.

关键词： Adaptive hierarchical graph attention Lightweight Siamese network Visual object tracking

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Transmission-Constrained Consensus of Multiagent Networks

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IEEE Transactions on Control of Network Systems 2023年第3期10卷 1484-1495页

作者： Wang, Xiaotian Su, Housheng Huazhong University of Science and Technology School of Artificial Intelligence and Automation Hubei430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

This article studies the consensus problem for multiagent systems with transmission constraints. A novel model of multiagent systems is proposed where the information transmissions between agents are disturbed by irregular distortions or interferences (named transmission constraint functions), and this model is universal which can be applied in many cases, such as interval consensus and discarded consensus. In the transmission-constrained consensus problem, we obtain the necessary and sufficient condition that agents can converge to state consensus. Furthermore, a more general case is studied in which the system reaches an equilibrium. Based on some techniques of stability theory, the existence, uniqueness, and stability of the system equilibrium point can be proven, which means the system can reach an asymptotically stable equilibrium. Moreover, the state values of the equilibrium are only decided by the network structure and transmission constraint functions but not the agents' initial states. Finally, numerical simulations are presented to illustrate the proposed theorems and corollaries. © 2014 IEEE.

关键词： Multi agent systems

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FIFAWC:a dataset with detailed annotation and rich semantics for group activity recognition

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Frontiers of Computer Science 2024年第6期18卷 271-272页

作者： Duoxuan PEI Di HUANG Yunhong WANG State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Intelligent Recognition and Image Processing Lab. School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

1 *** Activity Recognition(GAR),which aims to identify activities performed collectively in videos,has gained significant attention *** conventional action recognition centered on single individuals,GAR explores the c... 详细信息

关键词： has collective gained

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Privacy and Security in Ubiquitous Integrated Sensing and Communication: Threats, Challenges and Future Directions

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IEEE Internet of Things Magazine 2024年第4期7卷 52-58页

作者： Qu, Kaiqian Ye, Jia Li, Xuran Guo, Shuaishuai School of Control Science and Engineering Shandong University China Shandong University Shandong Key Laboratory of Wireless Communication Technologies China School of Electrical Engineering Chongqing University China School of Physics and Electronics Shandong Normal University Shandong Key Laboratory of Medical Physics and Image Processing China

Integrated sensing and communication (ISAC) technology is at the forefront of next-generation communication, enhancing applications from intel-ligent transportation to unmanned aerial vehicle surveillance and healthcare through ubiquitous sensing capability. However, the advent of ISAC brings with it a dual-edged challenge. While it opens up new avenues for application, it also raises significant concerns regarding the privacy of sensitive data and the security of systems in an inherently open environment. To navigate these challenges and unlock ISAC's full potential, this article starts with an analysis of the underlying factors that contribute to privacy and security vulnerabilities. It also identifies the technical obstacles that stand in the way of achieving a secure and private ISAC ecosystem within the confines of conventional network frameworks. As a solution, we introduce a security and privacy-preserving network (SPPN), designed to mitigate these potential threats and tackle the technical challenges through a secure framework for information handling and collaborative efforts among trusted parties, ISAC operators, and users. Central to SPPN's security strategies is an artificial intelligence based system, equipped to detect unauthorized access and coordinate defense mechanisms, including deploying friendly jammers to thwart malicious devices and utilizing reconfigurable intelligent surfaces (RISs) to bolster the network's defense mechanisms against potential attacks. Through detailed analysis and case studies, this article demonstrates the effectiveness of the SPPN framework, which not only strengthens the network's defenses but also significantly improves its sensing and communication capabilities. © 2018 IEEE.

关键词： Sensitive data

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