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arXiv 2022年

作者： Zhu, Yabin Li, Chenglong Liu, Yao Wang, Xiao Tang, Jin Luo, Bin Huang, Zhixiang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing Anhui Higher Education Institutes Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Hefei230601 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China School of Computer Science and Technology Anhui University Hefei230601 China Peng Cheng Laboratory Shenzhen China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing Anhui Higher Education Institutes Anhui University Hefei230601 China

Tiny objects, frequently appearing in practical applications, have weak appearance and features, and receive increasing interests in meany vision tasks, such as object detection and segmentation. To promote the research and development of tiny object tracking, we create a large-scale video dataset, which contains 434 sequences with a total of more than 217K frames. Each frame is carefully annotated with a high-quality bounding box. In data creation, we take 12 challenge attributes into account to cover a broad range of viewpoints and scene complexities, and annotate these attributes for facilitating the attribute-based performance analysis. To provide a strong baseline in tiny object tracking, we propose a novel Multilevel Knowledge Distillation Network (MKDNet), which pursues three-level knowledge distillations in a unified framework to effectively enhance the feature representation, discrimination and localization abilities in tracking tiny objects. Extensive experiments are performed on the proposed dataset, and the results prove the superiority and effectiveness of MKDNet compared with state-of-the-art methods. The dataset, the algorithm code, and the evaluation code are available at https://***/mmic-lcl/Datasets-andbenchmark-code. Copyright © 2022, The Authors. All rights reserved.

关键词： Distillation

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Fuzzy Asynchronous Fault Tolerant Control for Semi-Markov Jump Systems

Fuzzy Asynchronous Fault Tolerant Control for Semi-Markov Ju...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Kaixuan Chen Shuping He Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9781665438575

This work investigates the fault-tolerant control scheme for Takagi-Sugeno fuzzy semi-Markov jump systems with actuator faults. The hidden semi-Markov model is employed to describe the asynchronous phenomenon between the controller and plant. Based on Lyapunov theory, the fault tolerant controller depending on observable mode is presented to make sure that the semi-Markov jump systems is stochastically stable and satisfies the $H_{\infty}$ performance. A simulation example via a single-link robot is employed to prove the correctness of the studied approach.

关键词： Actuators Sufficient conditions Computational modeling Fault tolerant systems Fault tolerant control Manipulators Takagi-Sugeno model

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Nonmonotonic propositional logic

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Frontiers of Computer Science 2021年第3期15卷 215-216页

作者： Wei LI Yuefei SUI Yuhui WANG State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China School of Computer and Control Engineering University of Chinese Academy of SciencesBeijing 100049China Information Technology Center China Reinsurance(Group)CorporationBeijing 100033China

Propositional logic[1]is basic,based on which other logics are *** deduction system for propositional logic is *** logics are a class of logics which deduction systems are *** ones are default logic[2,3],R-calculus[4]... 详细信息

关键词： default propositional Nonmonotonic

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Robust DOA Estimation Based on Dual Lawson Norm for RIS-Aided Wireless Communication Systems

arXiv

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arXiv 2024年

作者： Yu, Canping Li, Yingsong Li, Liping Huang, Zhixiang Wu, Qingqing de Lamare, Rodrigo C. The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei230601 China The Department of Electronic Engineering Shanghai Jiao Tong University 200240 China Gávea 22451-900 Brazil The School of Physics Engineering and Technology University of York YorkYO10 5DD United Kingdom

Reconfigurable intelligent surfaces (RIS) can actively perform beamforming and have become a crucial enabler for wireless systems in the future. The direction-of-arrival (DOA) estimates of RIS received signals can help design the reflection control matrix and improve communication quality. In this paper, we design a RIS-assisted system and propose a robust Lawson norm-based multiple-signal-classification (LN-MUSIC) DOA estimation algorithm for impulsive noise environments, which is divided into two parts: first, the non-convex Lawson norm is used as the error criterion along with a regularization constraint to formulate the optimization problem. Then, a Bregman distance based alternating-direction-method-of-multipliers (ADMM) is used to solve the problem and recover the desired signal. The second part is to use the multiple-signal-classification (MUSIC) to find out the DOAs of targets based on their sparsity in the spatial domain. In addition, we also propose a RIS control matrix optimization strategy that requires no channel state information (CSI), which effectively enhances the desired signals and improves the performance of the LN-MUSIC algorithm. A Cramér–Rao-lower-bound (CRLB) of the proposed DOA estimation algorithm is presented and verifies its feasibility. Simulated results show that the proposed robust DOA estimate algorithm based on the Lawson norm can effectively suppress the impact of large outliers caused by impulsive noise on the estimation results, outperforming existing *** Codes - Copyright © 2024, The Authors. All rights reserved.

关键词： Impulse noise

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Error Analysis of Virtual Element Method for the Poisson-Boltzmann Equation

arXiv

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arXiv 2023年

作者： Huang, Linghan Shu, Shi Yang, Ying Guangxi Guilin541004 China School of Mathematics and Computational Science Xiangtan University Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Hunan Xiangtan411105 China Guangxi541004 China

The Poisson-Boltzmann equation is a nonlinear elliptic equation with Dirac distribution sources, which has been widely applied to the prediction of electrostatics potential of biological biomolecular systems in solution. In this paper, we discuss and analysis the virtual element method for the Poisson-Boltzmann equation on general polyhedral meshes. Under the low regularity of the solution of the whole domain, nearly optimal error estimates in both L2-norm and H1-norm for the virtual element approximation are obtained. The numerical experiment on different polyhedral meshes shows the efficiency of the virtual element method and verifies the proposed theoretical prediction. Copyright © 2023, The Authors. All rights reserved.

关键词： Poisson equation

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Learning to Learn Transferable Generative Attack for Person Re-Identification

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IEEE Transactions on Image processing 2025年 PP卷 PP页

作者： Bian, Yuan Liu, Min Wang, Xueping Ma, Yunfeng Wang, Yaonan Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China

Deep learning-based person re-identification (reid) models are widely employed in surveillance systems and inevitably inherit the vulnerability of deep networks to adversarial attacks. Existing attacks merely consider cross-dataset and cross-model transferability, ignoring the cross-test capability to perturb models trained in different domains. To powerfully examine the robustness of real-world re-id models, the Meta Transferable Generative Attack (MTGA) method is proposed, which adopts meta-learning optimization to promote the generative attacker producing highly transferable adversarial examples by learning comprehensively simulated transfer-based crossmodel&dataset&test black-box meta attack tasks. Specifically, cross-model&dataset black-box attack tasks are first mimicked by selecting different re-id models and datasets for meta-train and meta-test attack processes. As different models may focus on different feature regions, the Perturbation Random Erasing module is further devised to prevent the attacker from learning to only corrupt model-specific features. To boost the attacker learning to possess cross-test transferability, the Normalization Mix strategy is introduced to imitate diverse feature embedding spaces by mixing multi-domain statistics of target models. Extensive experiments show the superiority of MTGA, especially in cross-model&dataset and cross-model&dataset&test attacks, our MTGA outperforms the SOTA methods by 20.0% and 11.3% on mean mAP drop rate, respectively. © 1992-2012 IEEE.

关键词： Generative adversarial networks

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Stress recognition based on graph structure representation of facial StO2

Stress recognition based on graph structure representation o...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jiaxiu Wang Xinyu Liu Yingjuan Jia Tong Chen Jingru Huang Zheyuan Zhang College of Electronic and Information Engineering Southwest University Chongqing China Institute of Legal Psychology and Intelligent Computing Southwest University Chongqing China Chongqing Key Laboratory of Non-Linear Circuits and Intelligent Information Processing Southwest University Chongqing China

Stress is an integral state that affects physical and mental health of individuals. Tissue Oxygen Saturation (StO2) is an emerging physiological signal and can reflect different stress states. Previous studies have simply extracted features of StO2 from specific regions of the face without exploring potential associations between them. In this paper, we analyze the facial Region of Interest (ROI) based on StO2, so as to explore the deep relationship between ROIs. Building upon this, we construct, for the first time, a StO2-based facial graph structure for stress recognition by using ROIs as nodes. In addition, we propose a new graph pooling method called FTPool which allows to measure node significance in terms of both node characteristics and graph topology. Finally, we further propose a dual-stream network (GCNet) combining GNN and CNN for the baseline-independent stress recognition. The experimental results show that the proposed GCNet can achieve state-of-the-art (SOTA) results with an accuracy of 78.57% on the original unbalanced database.

关键词：

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DDoS Detection and Defense Based on FLAD and SDN

DDoS Detection and Defense Based on FLAD and SDN

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Jie Dong Wenyu Fang Wanling Zheng Jinkun Liu Yanhua Liu College of Computer and Data Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou China

ISBN: (数字)9798350356328

ISBN: (纸本)9798350356335

In order to achieve more efficient and accurate DDoS detection while ensuring data privacy, this paper proposes a DDoS detection method based on FLAD. Firstly, this paper uses the FLAD algorithm to train a global DDoS detection model without leaving local traffic data, protecting the privacy and security of traffic data between different hosts, and improving aggregation efficiency by dynamically adjusting the aggregation weights to adapt to different sub-dataset increments. Secondly, a DDoS traffic detection method based on the integration of LSTM and CNN is proposed, which extracts and analyzes the temporal correlation of traffic data by calculating the statistical characteristics of traffic data within a time period, to achieve real-time detection of traffic feature data. Again, combined with the concept of SDN, real-time defense against DDoS based on ODL-API is implemented, and precise matching of DDoS detection results with network entity information is achieved, realizing the technology of real-time and precise issuance of multiple flow rules, effectively blocking DDoS malicious attack traffic, protecting important entities in the topology, and maintaining stable traffic in the topology. This paper focuses on solving the detection problem of DDoS traffic data increments and uneven data distribution through the FLAD algorithm. Experimental results show that the proposed method improves the accuracy of DDoS attack detection by more than 4% and the F1 Score by more than 7% compared to the FedAvg aggregation algorithm.

关键词： Training Data privacy Network topology Denial-of-service attack Feature extraction Real-time systems Topology Labeling Computer crime Long short term memory

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Difference in Uptake Pattern Heterogeneity and Reproducibility of Radiomics Features Between FAPI and FDG Pet/Ct Imaging of Tumors

Difference in Uptake Pattern Heterogeneity and Reproducibili...

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IEEE International Symposium on Biomedical Imaging

作者： Tianmeng Xu Yanchao Huang Tingting Ang Shuilin Chu Peiyin Luo Shunfang Wang Yufeng Zhang Lijun Lu Ganghua Tang Wenbing Lv School of Information and Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China Department of Nuclear Medicine Laboratory for Quality Control and Evaluation of Radiopharmaceuticals Nanfang Hospital Southern Medical University Guangzhou China School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University Guangzhou China

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

To investigate the difference in uptake pattern heterogeneity between fluorodeoxyglucose (FDG) and fibroblast activation protein inhibitor (FAPI) PET/CT and the reproducibility of radiomics features with respect to different calculation methods of standardized uptake value (SUV). 210 patients with various tumors were involved. Among the extracted 497 radiomics features, there are only 20 features that exhibited an ICC difference of more than 0.25 between the two tracers when using different SUV calculation methods, revealing the similar influence of SUV calculation methods. In contrast, the ICC values for most texture features were generally lower (0.22-0.39) between FDG and FAPI PET images, indicating a large difference in uptake pattern heterogeneity between the two tracers. Our results demonstrated that the influence of SUV calculation methods on the reproducibility of FDG and FAPI PET features is similar. The uptake pattern heterogeneity characterized by radiomics features between FDG and FAPI PET images is significantly different.

关键词： Proteins Protein engineering Inhibitors Fibroblasts Feature extraction Reproducibility of results Radiomics

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Hidden Attractors in a Delayed Memristive Differential System with Fractional Order and Chaos Synchronization

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Journal of Harbin Institute of Technology(New Series) 2020年第1期27卷 67-75页

作者： Dawei Ding Yecui Weng Nian Wang School of Electronics and Information Engineering Anhui UniversityHefei 230601China Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui UniversityHefei 230601China

As an important research branch,memristor has attracted a range of scholars to study the property of memristive chaotic ***,time⁃delayed systems are considered a significant and newly⁃developing field in modern *** combining memristor and time⁃delay,a delayed memristive differential system with fractional order is proposed in this paper,which can generate hidden ***,we discussed the dynamics of the proposed system where the parameter was set as the bifurcation parameter,and showed that with the increase of the parameter,the system generated rich chaotic phenomena such as bifurcation,chaos,and *** we derived adequate and appropriate stability criteria to guarantee the system to achieve ***,examples were provided to analyze and confirm the influence of parameter a,fractional order q,and time delayτon chaos *** simulation results confirm that the chaotic synchronization is affected by a,q andτ.

关键词： fractional order memristive time⁃delay hidden attractors chaos synchronization

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