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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Siting Tao Zhi Zhang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan China China

ISBN: (纸本)9781665409858

At present, most of the video-based 3D human pose estimation methods process the video frame by frame, ignoring the timing information of the upper and lower frames of the video. When there is a single-frame estimation error caused by self-occlusion, the occlusion part will be Some strange movements appear due to information loss, and the estimated results make it difficult to produce accurate motion sequences. Therefore, considering the continuity of the upper and lower frames of the video, this paper adopts the HMR algorithm and introduces a bidirectional long-term memory network (BI-LSTM) in the encoding part to process the video sequence, and then outputs the parameters of the human body model through the SMPL parameters and inputs them into the discriminator for confrontation, train. In order for the discriminator to also take into account the semantic information of the temporal context, the discriminator in this paper also introduces a BI-LSTM network to improve the authenticity of the generated poses. Experimental results show that the accuracy of the model is improved when self-occlusion occurs.

关键词： Training Industrial electronics Solid modeling Estimation error Three-dimensional displays Biological system modeling Pose estimation

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Unified Dual-view Cognitive Model for Interpretable Claim Verification

arXiv

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arXiv 2021年

作者： Wu, Lianwei Rao, Yuan Lan, Yuqian Sun, Ling Qi, Zhaoyin Xi’an Key Lab. of Social Intelligence and Complexity Data Processing School of Software Engineering Xi’an Jiaotong University China China Research Institute of Xi’an Jiaotong University Shenzhen China

Recent studies constructing direct interactions between the claim and each single user response to capture evidence have shown remarkable success in interpretable claim verification. Owing to different single responses convey different cognition of individual users, the captured evidence belongs to the perspective of individual cognition. However, individuals’ cognition of social things is not always able to truly reflect the objective. There may be one-sided or biased semantics in their opinions on a claim. The captured evidence correspondingly contains some unobjective and biased information. In this paper, we propose a Dual-view model based on the views of Collective and Individual Cognition (CICD) for interpretable claim verification. For collective cognition, we not only capture the word-level semantics based on individual users, but also focus on sentence-level semantics (i.e., the overall responses) among all users to generate global evidence. For individual cognition, we select the top-k articles with high degree of difference and interact with the claim to explore the local key evidence fragments. To weaken the bias of individual cognition-view evidence, we devise an inconsistent loss to suppress the divergence between global and local evidence for strengthening the consistent shared evidence between the both. Experiments on three benchmark datasets confirm the effectiveness of CICD. © 2021, CC BY.

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Hexagonally ordered microbowl arrays decorated with ultrathin CuInS_(2) nanosheets for enhanced photoelectrochemical performance

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Journal of Energy Chemistry 2020年第12期29卷 134-142页

作者： Ming Li Le Chen Yanjie Su Huan Yin Kexiang Hu State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyKey Laboratory of Optoelectronic Information Processing of Guangxi Colleges and Uniy/ersitiesGuilin 541004GuangxiChina Key Laboratory for Thin Film and Microfabrication of the Ministry of Education Department of Micro/Nano ElectronicsSchool of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China National and Local Joint Engineering Laboratory of Internet Technology on Mine School of Information and Control EngineeringChina University of Mining and TechnologyXuzhou 221008JiangsuChina School of Physics and Telecommunication Engineering Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data ProcessingYulin Normal UniversityYulin 537400GuangxiChina

This paper demonstrates the design and fabrication of three-dimensional(3 D) hexagonally ordered microbowl arrays(MBAs) decorated with Cu In S2 nanosheets for enhanced photoelectrochemical(PEC) performance. The 3 D MBAs are fabricated by a micro-fabrication technique. The ultrathin CuInS2 nanosheets are grown on the 3 D electrodes by solvothermal transformation of Cu film. The photocurrent density of 3 D photocathode(CuInS2@MBAs) is about two times higher than that of the planar counterpart(CuInS2@Planar). The improved PEC performance can be ascribed to the elevated light trapping ability and the increased surface area for loading photocatalysts. In addition, CdS quantum dots as cocatalysts are modified onto the Cu In S2 nanosheets to further enhance the PEC activity because the formed p-n heterojunction can accelerate the separation of photogenerated carriers. As a result, the 3 D photocathode of CuInS2/CdS@MBAs shows an optimal incident photon to current efficiency of 10% at the wavelength of400 nm. It is believed that this work can be generalized to design other hierarchical 3 D photoelectrodes for improved solar water splitting.

关键词： Microbowl array CuInS_(2) Nanosheet Photocathode Photoelectrochemical performance

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Potential impact of noise correlation in next-generation gravitational wave detectors

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Physical Review D 2025年第4期111卷 044046-044046页

作者： Isaac C. F. Wong Peter T. H. Pang Milan Wils Francesco Cireddu Walter Del Pozzo Tjonnie G. F. Li KU Leuven Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics Kasteelpark Arenberg 10 3001 Leuven Belgium Leuven Gravity Institute KU Leuven Celestijnenlaan 200D box 2415 3001 Leuven Belgium Institute for Gravitational and Subatomic Physics (GRASP) Utrecht University Princetonplein 1 3584 CC Utrecht The Netherlands Nikhef Science Park 105 1098 XG Amsterdam The Netherlands Institute for Theoretical Physics KU Leuven Celestijnenlaan 200D B-3001 Leuven Belgium Dipartimento di Fisica “E. Fermi ” Università di Pisa I-56127 Pisa Italy INFN Sezione di Pisa I-56127 Pisa Italy

Building upon the statistical formulation for parameter estimation in the presence of correlated noise proposed by Cireddu et al., we present the initial study to incorporate the effects of correlated noise into the analyses of various detector designs’ performance. We consider a two-L-shaped-detector configuration located in Europe and compare the expectation of parameter estimation of gravitational wave transients between noncollocated and hypothetical collocated configurations. In our study, we posit the existence of low-frequency correlated noise within the 5–10 Hz range for the collocated detector configuration, with a varying degree of correlation. In this specific detector setup, our observations indicate an enhancement in the precision of intrinsic parameter measurements as the degree of correlation increases. This trend suggests that higher degrees of noise correlation may beneficially influence the accuracy of parameter estimation. In particular, when the noise is highly correlated, the uncertainty on chirp mass decreases by up to 30%. The absence of an inter-European baseline does hinder the estimation of the extrinsic parameters. However, given a realistic global network with the additional detector located in the United States, the uncertainty of extrinsic parameters is significantly reduced. This reduction is further amplified as the degree of noise correlation increases. When the degree of noise correlation exceeds a certain level, the collocated configuration outperforms the noncollocated configuration. For instance, when the degree of correlation is high, the collocated configuration decreases the 90% credible area of sky location by up to 10% compared to the noncollocated configuration. We conclude that the impact of noise correlation is not trivial and can potentially alter both the quantitative and qualitative outcomes in detector performance. We therefore recommend the inclusion of noise correlation for a comprehensive assessment of the design o

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Multi-Task Diffusion Incentive Design for Mobile Crowdsourcing in Social Networks

arXiv

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arXiv 2023年

作者： Guo, Jianxiong Ni, Qiufen Wu, Weili Du, Ding-Zhu The Advanced Institute of Natural Sciences Beijing Normal University Zhuhai519087 China The Guangdong Key Lab of AI and Multi-Modal Data Processing BNU-HKBU United International College Zhuhai519087 China The School of Computers Guangdong University of Technology Guangzhou510006 China The Department of Computer Science Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas RichardsonTX75080 United States

Mobile Crowdsourcing (MCS) is a novel distributed computing paradigm that recruits skilled workers to perform location-dependent tasks. A number of mature incentive mechanisms have been proposed to address the worker recruitment problem in MCS systems. However, they all assume that there is a large enough worker pool and a sufficient number of users can be selected. This may be impossible in large-scale crowdsourcing environments. To address this challenge, we consider the MCS system defined on a location-aware social network provided by a social platform. In this system, we can recruit a small number of seed workers from the existing worker pool to spread the information of multiple tasks in the social network, thus attracting more users to perform tasks. In this paper, we propose a Multi-Task Diffusion Maximization (MT-DM) problem that aims to maximize the total utility of performing multiple crowdsourcing tasks under the budget. To accommodate multiple tasks diffusion over a social network, we create a multi-task diffusion model, and based on this model, we design an auction-based incentive mechanism, MT-DM-L. To deal with the high complexity of computing the multi-task diffusion, we adopt Multi-Task Reverse Reachable (MT-RR) sets to approximate the utility of information diffusion efficiently. Through both complete theoretical analysis and extensive simulations by using real-world datasets, we validate that our estimation for the spread of multitask diffusion is accurate and the proposed mechanism achieves individual rationality, truthfulness, computational efficiency, and (1 − 1/√e − Ε) approximation with at least 1 − δ probability. Copyright © 2023, The Authors. All rights reserved.

关键词： Approximation algorithms

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Group-wise Inhibition based Feature Regularization for Robust Classification

Group-wise Inhibition based Feature Regularization for Robus...

引用

International Conference on Computer Vision (ICCV)

作者： Haozhe Liu Haoqian Wu Weicheng Xie Feng Liu Linlin Shen Computer Vision Institute College of Computer Science and Software Engineering SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society National Engineering Laboratory for Big Data System Computing Technology Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

The convolutional neural network (CNN) is vulnerable to degraded images with even very small variations (e.g. corrupted and adversarial samples). One of the possible reasons is that CNN pays more attention to the most discriminative regions, but ignores the auxiliary features when learning, leading to the lack of feature diversity for final judgment. In our method, we propose to dynamically suppress significant activation values of CNN by group-wise inhibition, but not fixedly or randomly handle them when training. The feature maps with different activation distribution are then processed separately to take the feature independence into account. CNN is finally guided to learn richer discriminative features hierarchically for robust classification according to the proposed regularization. Our method is comprehensively evaluated under multiple settings, including classification against corruptions, adversarial attacks and low data regime. Extensive experimental results show that the proposed method can achieve significant improvements in terms of both robustness and generalization performances, when compared with the state-of-the-art methods. Code is available at https://***/LinusWu/TENET_Training.

关键词： Training Computer vision Codes Heuristic algorithms Robustness Classification algorithms Convolutional neural networks

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Permutation polynomials x~(2k+1+3)+ax2k+2+bx over F_(22k) and their differential uniformity

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Science China(Information Sciences) 2020年第10期63卷 255-257页

作者： Jie PENG Lijing ZHENG Chunsheng WU Haibin KAN Mathematics and Science College Shanghai Normal University School of Mathematics and Physics University of South China Department of Mathematics Lianyungang Normal University Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan University Fudan-Zhongan Joint Laboratory of Blockchain and Information Security Shanghai Blockchain Engineering Research Center Shanghai Institute for Advanced Communication and Data Science Shanghai Institute of Intelligent Electronics & Systems

Dear editor,A polynomial f（x）∈Fq[x] is called a permutation polynomial （PP） over the finite field Fq if the associated mapping f:c （?） f（c） from Fq to itself is bijective.A PP f is called a complete permutation polynomial if f（x）+x is a *** over finite fields of even characteristic have wide applications,including cryptography,coding theory,and communication *** many block ciphers with substitution-permutation network structure,the substitution box is usually a PP over F_(22k)for some positive integer *** resist the differential attacks,the differential uniformity of this

关键词： Finite fields Permutation polynomial Binomial Trinomial Differential uniformity

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A Fuzzy ESO-based Joint Angle Control Design of Snake Robots

A Fuzzy ESO-based Joint Angle Control Design of Snake Robots

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IEEE International Conference on Robotics and Biomimetics

作者： Lili Wu Yang Liu Junfang Zhou Zhigang Wang Yushuang Wang Yongchen Tang Beijing Electro-Mechanical Engineering Institute Beijing China 91039 Army School of Electrical and Information Engineering Tianjin University Tianjin China Key Lab of Intelligent Data Information Processing and Control of Hebei Province Tangshan University Tangshan China

ISBN: (纸本)9781665405362

The joint angle control of snake robot is an important component for the path tracking control. However, existing controllers can not realize the accurate control of the joint angle of snake robots since they rely on model information and can not adapt to the uncertain environment. Here, aiming at the above problems, a fuzzy extended state observer (FESO)-based joint angle controller for snake robots is designed. The total system disturbance including model uncertainty and external disturbance is estimated by FESO and then rejected by adding a corresponding part to the control law. Moreover, the peaking phenomenon caused by initial estimation errors can be suppressed in the proposed FESO. Finally, the effectiveness of the designed joint angle controller is verified by simulations.

关键词： Adaptation models Estimation error Uncertainty Control design Conferences Biomimetics Biological system modeling

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Robust Adaptive Beamforming via Worst-Case SINR Maximization with Nonconvex Uncertainty Sets

arXiv

引用

arXiv 2022年

作者： Huang, Yongwei Fu, Hao Vorobyov, Sergiy A. Luo, Zhi-Quan School of Information Engineering Guangdong University of Technology University Town Guangdong Guangzhou510006 China Huawei Technologies Software Avenue Yuhuatai District Jiangsu Nanjing China The Department of Signal Processing and Acoustics Aalto University Espoo02150 Finland School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen Research Institute of Big Data Guangdong518172 China

This paper considers a formulation of the robust adaptive beamforming (RAB) problem based on worst-case signal-to-interference-plus-noise ratio (SINR) maximization with a nonconvex uncertainty set for the steering vectors. The uncertainty set consists of a similarity constraint and a (nonconvex) double-sided ball constraint. The worst-case SINR maximization problem is turned into a quadratic matrix inequality (QMI) problem using the strong duality of semidefinite programming. Then a linear matrix inequality (LMI) relaxation for the QMI problem is proposed, with an additional valid linear constraint. Necessary and sufficient conditions for the tightened LMI relaxation problem to have a rank-one solution are established. When the tightened LMI relaxation problem still has a high-rank solution, the LMI relaxation problem is further restricted to become a bilinear matrix inequality (BLMI) problem. We then propose an iterative algorithm to solve the BLMI problem that finds an optimal/suboptimal solution for the original RAB problem by solving the BLMI formulations. To validate our results, simulation examples are presented to demonstrate the improved array output SINR of the proposed robust beamformer. © 2022, CC BY-NC-SA.

关键词： Linear matrix inequalities

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Dual Templates Siamese Tracking 5th

Dual Templates Siamese Tracking

引用

5th Asian Conference on Pattern Recognition, ACPR 2019

作者： Hou, Zhiqiang Chen, Lilin Pu, Lei Institute of Computer Xi’an University of Posts and Telecommunications Xi’an710121 China Information and Navigation Institute of Air Force Engineering University Xi’an710077 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an University of Posts and Telecommunications Xi’an710121 China

ISBN: (纸本)9783030414030

In recent years, Siamese networks which is based on appearance similarity comparison strategy has attracted great attention in visual object tracking domain due to its balanced accuracy and speed. However, most Siamese networks based tracking algorithms have not considered template updates. The fixed template may cause tracking matching error and can even cause failure of object tracking. In view of this deficiency, we proposed an algorithm based on dual templates Siamese network using difference hash algorithm to determine the template update timing. First, we kept the initial frame target with stable response map score as the base template zr, using the difference hash algorithm to determine the dynamic template zt. We analyzed the candidate targets region and the two template matching results, meanwhile the result response maps were fused, which could ensure more accurate tracking results. The experiment results on the OTB-2013 and OTB-2015 and VOT2016 datasets showed that the proposed algorithm has achieved satisfactory result. © Springer Nature Switzerland AG 2020.

关键词： Template matching

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