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Ocean image data augmentation in the USV virtual training scene

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Big Earth Data 2020年第4期4卷 451-463页

作者： Wei Wang Yang Li Xiangfeng Luo Shaorong Xie school of computer Engineering and science Shanghai UniversityShanghaiChina

The rapid development of intelligent navigation drives the rapid accumulation of ocean data,and the ocean science has entered the era of big ***,the complexity and variability of the ocean environments make some data *** makes ocean target detection and the unmanned surface vehicle(USV)intelligent control process in ocean scenarios face various challenges,such as the lack of training data and training *** ocean image data collection method used to capture images of complex ocean environments is costly,and it leads to a serious shortage of ocean scene image *** addition,the construction of an autonomous learning environment is crucial but *** order to solve the above problems,we propose a data collection method using virtual ocean scenes and the USV intelligent training *** on virtual ocean scenes,we obtain rare images of ocean scenes under complex weather conditions and implement the USV intelligent control training *** results show that the accuracy of ocean target detection and the success rate of obstacle avoidance of the USV are improved based on the virtual ocean scenes.

关键词： Virtual ocean scenes data augmentation intelligent control training USV obstacle avoidance

Dynamic Load Balancing Based on Restricted Multicast Tree in Homogeneous Multiprocessor Systems

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Journal of Beijing Institute of Technology 2008年第2期17卷 184-188页

作者：刘滨石峰高玉金 school of computer science and Technology Beijing Institute of Technology

To decrease the cost of exchanging load information among processors, a dynamic load-balancing （DLB） algorithm which adopts multieast tree technology is proposed. The muhieast tree construction rules are also proposed to avoid wrongly transferred or redundant DLB messages due to the overlapping of multicast trees. The proposed DLB algorithm is distributed controlled, sender initiated and can help heavily loaded processors with complete distribution of redundant loads with minimum number of executions. Experiments were executed to compare the effects of the proposed DLB algorithm and other three ones, the results prove the effectivity and practicability of the proposed algorithm in dealing with great scale compute-intensive tasks.

关键词： dynamic load balancing (DLB) multicast tree rule message Multiprocessor

electrical-Controlled Transport for Surface States in a Dirac Semimetal Quantum Wire

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Chinese Physics Letters 2015年第12期32卷 117-120页

作者：肖贤波刘正方何扬名李会丽艾国平杜琰 school of computer science Jiangxi University of Traditional Chinese Medicine Nanchang 330004 school of Basic science East China diaotong University Nanchang 330013

The transport properties of a Dirac semimet^l quantum wire with two side gates are theoretically studied by adopting the lattice Green function method. It is found that a residual conductance quantum contributed from the surface states can be switched on or off by tuning the electron energy or the side gates voltage. This ideal switching effect for the surface Dirac electron results from the transversal quantum confinement of the quantum wire in combination with the electrostatic potential induced by the side gates. These findings may provide useful guidance for designing all-electrical topological nanoelectronic devices.

关键词： electrical-Controlled Transport for Surface States in a Dirac Semimetal Quantum Wire DSM

Leaderless and leader-following consensus of linear multi-agent systems

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Chinese Physics B 2014年第11期23卷 136-144页

作者：张晓娇崔宝同娄柯 school of computer science and Control Engineering North University of China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University College of electrical Engineering Anhui Polytechnic University

This paper studies the consensus problems for multi-agent systems with general linear and nonlinear dynamics. The leaderless and leader-following consensus problems are investigated respectively. Contraction theory is employed to gen- erate some sufficient conditions for testing the agents reaching consensus. Under these conditions and certain assumptions, the trajectories of multi-agent systems in directed topology will converge to each other. Finally, two numerical examples are given to illustrate the effectiveness of the proposed results,

关键词： linear multi-agent systems contraction theory virtual system partial contraction

Supervised and Semi-supervised Methods for Abdominal Organ Segmentation: A Review

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International Journal of Automation and computing 2021年第6期18卷 887-914页

作者： Isaac Baffour Senkyire Zhe Liu school of computer science and Communication Engineering Jiangsu UniversityZhenjiang 212013China computer science Department Ghana Communication Technology UniversityAccraGhana

Abdominal organ segmentation is the segregation of a single or multiple abdominal organ(s) into semantic image segments of pixels identified with homogeneous features such as color and texture, and intensity. The abdominal organ(s) condition is mostly connected with greater morbidity and mortality. Most patients often have asymptomatic abdominal conditions and symptoms, which are often recognized late;hence the abdomen has been the third most common cause of damage to the human body. That notwithstanding,there may be improved outcomes where the condition of an abdominal organ is detected earlier. Over the years, supervised and semi-supervised machine learning methods have been used to segment abdominal organ(s) in order to detect the organ(s) condition. The supervised methods perform well when the used training data represents the target data, but the methods require large manually annotated data and have adaptation problems. The semi-supervised methods are fast but record poor performance than the supervised if assumptions about the data fail to hold. Current state-of-the-art methods of supervised segmentation are largely based on deep learning techniques due to their good accuracy and success in real world applications. Though it requires a large amount of training data for automatic feature extraction, deep learning can hardly be used. As regards the semi-supervised methods of segmentation, self-training and graph-based techniques have attracted much research attention. Self-training can be used with any classifier but does not have a mechanism to rectify mistakes early. Graph-based techniques thrive on their convexity, scalability, and effectiveness in application but have an out-of-sample problem. In this review paper, a study has been carried out on supervised and semi-supervised methods of performing abdominal organ segmentation. An observation of the current approaches, connection and gaps are identified, and prospective future research opportunities are enu

关键词： Abdominal organ supervised segmentation semi-supervised segmentation evaluation metrics image segmentation machine learning

POSITIVE DEFINITE AND SEMI-DEFINITE SPLITTING METHODS FOR NON-HERMITIAN POSITIVE DEFINITE LINEAR SYSTEMS

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Journal of Computational Mathematics 2016年第3期34卷 300-316页

作者： Na Huang Changfeng Ma school of Mathematics and computer science Fujian Normal University Fuzhou 350117 China

In this paper, we further generalize the technique for constructing the normal （or pos- itive definite） and skew-Hermitian splitting iteration method for solving large sparse non- Hermitian positive definite system of linear equations. By introducing a new splitting, we establish a class of efficient iteration methods, called positive definite and semi-definite splitting （PPS） methods, and prove that the sequence produced by the PPS method con- verges unconditionally to the unique solution of the system. Moreover, we propose two kinds of typical practical choices of the PPS method and study the upper bound of the spectral radius of the iteration matrix. In addition, we show the optimal parameters such that the spectral radius achieves the minimum under certain conditions. Finally, some numerical examples are given to demonstrate the effectiveness of the considered methods.

关键词： Linear systems Splitting method Non-Hermitian matrix Positive definitematrix Positive semi-definite matrix Convergence analysis.

Parameterization Transfer for a Planar Computational Domain in Isogeometric Analysis

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computer Modeling in Engineering & sciences 2023年第11期137卷 1957-1973页

作者： Jinlan Xu Shuxin Xiao Gang Xu Renshu Gu school of computer science and Technology Hangzhou Dianzi UniversityHangzhou310018China

In this paper,we propose a parameterization transfer algorithm for planar domains bounded by B-spline curves,where the shapes of the planar domains are *** domain geometries are considered to be similar if their simplified skeletons have the same *** domain we call source domain,and it is parameterized using multi-patch B-spline *** resulting parameterization is C1 continuous in the regular region and G1 continuous around singular points regardless of whether the parameterization of the source domain is C1/G1 continuous or *** this algorithm,boundary control points of the source domain are extracted from its parameterization as sequential points,and we establish a correspondence between sequential boundary control points of the source domain and the target boundary through discrete sampling and *** of the parametrization satisfies C1/G1 continuity under discrete harmonic mapping with continuous *** new algorithm has a lower calculation cost than a decomposition-based parameterization with a high-quality parameterization *** demonstrate that the result of the parameterization transfer in this paper can be applied in isogeometric ***,because of the consistency of the parameterization for the two models,this method can be applied in many other geometry processing algorithms,such as morphing and deformation.

关键词： Isogeometric analysis parameterization transfer discrete harmonic mapping C1/G1 continuity

DRO-SLAM: real-time object-aware SLAM for navigation robots and autonomous driving in dynamic environments

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The Journal of China Universities of Posts and Telecommunications 2023年第3期30卷 14-24页

作者： Wang Zixian Zhang Miao Yan Danfeng school of computer science Beijing University of Posts and TelecommunicationsBeijing 100876China

Traditional simultaneous localization and mapping(SLAM) mostly performs under the assumption of an ideal static environment, which is not suitable for dynamic environments in the real world. Dynamic real-time object-aware SLAM(DRO-SLAM) is proposed in this paper, which is a visual SLAM that can realize simultaneous localizing and mapping and tracking of moving objects indoor and outdoor at the same time. It can use target recognition, oriented fast and rotated brief(ORB) feature points, and optical flow assistance to track multi-target dynamic objects and remove them during dense point cloud reconstruction while estimating their pose. By verifying the algorithm effect on the public dataset and comparing it with other methods, it can be obtained that the proposed algorithm has certain guarantees in real-time and accuracy, it also provides more functions. DRO-SLAM can provide the solution to automatic navigation which can realize lightweight deployment, provide more vehicles, pedestrians and other environmental information for navigation.

关键词： simultaneous localization and mapping(SLAM) object tracking stereo vision dynamic environment data association

Specificity-preserving RGB-D saliency detection

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Computational Visual Media 2023年第2期9卷 297-317页

作者： Tao Zhou Deng-Ping Fan Geng Chen Yi Zhou Huazhu Fu school of computer science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Key Laboratory of System Control and Information Processing Ministry of EducationShanghaiChina computer Vision Lab ETH Z¨urichZ¨urichSwitzerland school of computer science and Engineering Northwestern Polytechnical UniversityXi’anChina school of computer science and Engineering Southeast UniversityNanjingChina Inception Institute of Artificial Intelligence Abu DhabiUnited Arab Emirates

Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few methods explicitly consider how to preserve modality-specific *** this study,we propose a novel framework,the specificity-preserving network(SPNet),which improves SOD performance by exploring both the shared information and modality-specific ***,we use two modality-specific networks and a shared learning network to generate individual and shared saliency prediction *** effectively fuse cross-modal features in the shared learning network,we propose a cross-enhanced integration module(CIM)and propagate the fused feature to the next layer to integrate cross-level ***,to capture rich complementary multi-modal information to boost SOD performance,we use a multi-modal feature aggregation(MFA)module to integrate the modalityspecific features from each individual decoder into the shared *** using skip connections between encoder and decoder layers,hierarchical features can be fully *** experiments demonstrate that our SPNet outperforms cutting-edge approaches on six popular RGB-D SOD and three camouflaged object detection *** project is publicly available at https://***/taozh2017/SPNet.

关键词： salient object detection(SOD) RGB-D cross-enhanced integration module(CIM) multi-modal feature aggregation(MFA)