Single object tracking based on deep learning has achieved the advanced performance in many applications of computer vision.However,the existing trackers have certain limitations owing to deformation,occlusion,movemen...Single object tracking based on deep learning has achieved the advanced performance in many applications of computer vision.However,the existing trackers have certain limitations owing to deformation,occlusion,movement and some other conditions.We propose a siamese attentional dense network called SiamADN in an end-to-end offline manner,especially aiming at unmanned aerial vehicle(UAV)tracking.First,it applies a dense network to reduce vanishing-gradient,which strengthens the features transfer.Second,the channel attention mechanism is involved into the Densenet structure,in order to focus on the possible key regions.The advance corner detection network is introduced to improve the following tracking process.Extensive experiments are carried out on four mainly tracking benchmarks as OTB-2015,UAV123,LaSOT and VOT.The accuracy rate on UAV123 is 78.9%,and the running speed is 32 frame per second(FPS),which demonstrates its efficiency in the practical real application.展开更多
Based on the analysis of application status in real network,the trace model of some typical mobile Internet applications data is given and their impact on 2G/3G network is discussed in this paper.Furthermore,in order ...Based on the analysis of application status in real network,the trace model of some typical mobile Internet applications data is given and their impact on 2G/3G network is discussed in this paper.Furthermore,in order to support the mobile Internet application efficiently in future,the issues including the impact on the Long Term Evolution (LTE-A) system and some potential solutions for performance optimization are studied.Based on the trace data model of IM traffic,the performacne evaluaiton of LTE-A system shows that some specific configuration machanisms can play an important role in improving network system efficiency in the case of IM traffic.展开更多
Recently, the community analysis has seen enormous research advancements in the field of social networks. A large amount of the current studies put forward different models and algorithms about most influential people...Recently, the community analysis has seen enormous research advancements in the field of social networks. A large amount of the current studies put forward different models and algorithms about most influential people. However, there is little work to shed light on how to rank communities while considering their levels that are determined by the quality of their published contents. In this paper, we propose solution for measuring the influence of communities and ranking them by considering joint weight composed of internal and external influence of communities. To address this issue, we design a novel algorithm called Com Rank: a modification of Page Rank, which considers the joint weight in order to identify impact of each community and ranking them. We use real-world data trace in citation network and perform extensive experiments to evaluate our proposed algorithm. The comparative results depict significant improvements by our algorithm in community ranking due to the inclusion of proposed weighting feature.展开更多
Mobile target tracking is a necessary function of some emerging application domains, such as virtual reality, smart home and intelligent healthcare. However, existing portable devices for target tracking are resource ...Mobile target tracking is a necessary function of some emerging application domains, such as virtual reality, smart home and intelligent healthcare. However, existing portable devices for target tracking are resource intensive and high-cost. Camera tracking is an effective location tracking way for those emerging applications which can reuse the existing ubiquitous video monitoring system. This paper proposes a dynamic community-based camera collaboration(D3C) framework for target location and tracking. The contributions of D3C mainly include that(1) nonlinear perspective projection model is selected as the camera sensing model and sequential Monte Carlo is employed to predict the target location;(2) a dynamic collaboration scheme is proposed, it is based on the local community-detection theory deriving from social network analysis. The performance of proposed approach is validated by both synthetic datasets and real-world application. The experiment results show that D3C meets the versatility, real-time and fault tolerance requirements of target tracking applications.展开更多
The interference alignment （IA） algorithm based on FDPM subspace tracking （FDPM-ST IA） is proposed for MIMO cognitive network （CRN） with multiple primary users in this paper. The feasibility conditions of FDPM-S...The interference alignment （IA） algorithm based on FDPM subspace tracking （FDPM-ST IA） is proposed for MIMO cognitive network （CRN） with multiple primary users in this paper. The feasibility conditions of FDPM-ST IA is also got. Futherly, IA scheme of secondary network and IA scheme of primary network are given respectively without assuming a priori knowledge of interference covariance matrices. Moreover, the paper analyses the computational complexity of FDPM-ST IA. Simulation results and theoretical calculations show that the proposed algorithm can achieve higher sum rate with lower computational complexity.展开更多
基金supported by the Zhejiang Key Laboratory of General Aviation Operation Technology(No.JDGA2020-7)the National Natural Science Foundation of China(No.62173237)+3 种基金the Natural Science Foundation of Liaoning Province(No.2019-MS-251)the Talent Project of Revitalization Liaoning Province(No.XLYC1907022)the Key R&D Projects of Liaoning Province(No.2020JH2/10100045)the High-Level Innovation Talent Project of Shenyang(No.RC190030).
文摘Single object tracking based on deep learning has achieved the advanced performance in many applications of computer vision.However,the existing trackers have certain limitations owing to deformation,occlusion,movement and some other conditions.We propose a siamese attentional dense network called SiamADN in an end-to-end offline manner,especially aiming at unmanned aerial vehicle(UAV)tracking.First,it applies a dense network to reduce vanishing-gradient,which strengthens the features transfer.Second,the channel attention mechanism is involved into the Densenet structure,in order to focus on the possible key regions.The advance corner detection network is introduced to improve the following tracking process.Extensive experiments are carried out on four mainly tracking benchmarks as OTB-2015,UAV123,LaSOT and VOT.The accuracy rate on UAV123 is 78.9%,and the running speed is 32 frame per second(FPS),which demonstrates its efficiency in the practical real application.
基金supported by the project"the Cross Layer Optimization Technique for IMT-Advanced " under Grant No.2010ZX03003-001-01-03
文摘Based on the analysis of application status in real network,the trace model of some typical mobile Internet applications data is given and their impact on 2G/3G network is discussed in this paper.Furthermore,in order to support the mobile Internet application efficiently in future,the issues including the impact on the Long Term Evolution (LTE-A) system and some potential solutions for performance optimization are studied.Based on the trace data model of IM traffic,the performacne evaluaiton of LTE-A system shows that some specific configuration machanisms can play an important role in improving network system efficiency in the case of IM traffic.
基金supported in part by the following funding agencies of China:National Natural Science Foundation under Grant 61170274, 61602050 and U1534201
文摘Recently, the community analysis has seen enormous research advancements in the field of social networks. A large amount of the current studies put forward different models and algorithms about most influential people. However, there is little work to shed light on how to rank communities while considering their levels that are determined by the quality of their published contents. In this paper, we propose solution for measuring the influence of communities and ranking them by considering joint weight composed of internal and external influence of communities. To address this issue, we design a novel algorithm called Com Rank: a modification of Page Rank, which considers the joint weight in order to identify impact of each community and ranking them. We use real-world data trace in citation network and perform extensive experiments to evaluate our proposed algorithm. The comparative results depict significant improvements by our algorithm in community ranking due to the inclusion of proposed weighting feature.
基金supported by National Natural Science Foundation of China (Grant No. 61501048) National High-tech R&D Program of China (863 Program) (Grant No. 2013AA102301)+1 种基金The Fundamental Research Funds for the Central Universities (Grant No. 2017RC12) China Postdoctoral Science Foundation funded project (Grant No.2016T90067, 2015M570060)
文摘Mobile target tracking is a necessary function of some emerging application domains, such as virtual reality, smart home and intelligent healthcare. However, existing portable devices for target tracking are resource intensive and high-cost. Camera tracking is an effective location tracking way for those emerging applications which can reuse the existing ubiquitous video monitoring system. This paper proposes a dynamic community-based camera collaboration(D3C) framework for target location and tracking. The contributions of D3C mainly include that(1) nonlinear perspective projection model is selected as the camera sensing model and sequential Monte Carlo is employed to predict the target location;(2) a dynamic collaboration scheme is proposed, it is based on the local community-detection theory deriving from social network analysis. The performance of proposed approach is validated by both synthetic datasets and real-world application. The experiment results show that D3C meets the versatility, real-time and fault tolerance requirements of target tracking applications.
基金the National Nature Science Foundation of China under Grant No.61271259 and 61301123,the Chongqing Nature Science Foundation under Grant No.CTSC2011jjA40006,and the Research Project of Chongqing Education Commission under Grant No.KJ120501 and KJ120502
文摘The interference alignment （IA） algorithm based on FDPM subspace tracking （FDPM-ST IA） is proposed for MIMO cognitive network （CRN） with multiple primary users in this paper. The feasibility conditions of FDPM-ST IA is also got. Futherly, IA scheme of secondary network and IA scheme of primary network are given respectively without assuming a priori knowledge of interference covariance matrices. Moreover, the paper analyses the computational complexity of FDPM-ST IA. Simulation results and theoretical calculations show that the proposed algorithm can achieve higher sum rate with lower computational complexity.
