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  • Open Access

    ARTICLE

    Learning Dual-Domain Calibration and Distance-Driven Correlation Filter: A Probabilistic Perspective for UAV Tracking

    Taiyu Yan1, Yuxin Cao1, Guoxia Xu1, Xiaoran Zhao2, Hu Zhu1, Lizhen Deng3,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3741-3764, 2023, DOI:10.32604/cmc.2023.039828

    Abstract Unmanned Aerial Vehicle (UAV) tracking has been possible because of the growth of intelligent information technology in smart cities, making it simple to gather data at any time by dynamically monitoring events, people, the environment, and other aspects in the city. The traditional filter creates a model to address the boundary effect and time filter degradation issues in UAV tracking operations. But these methods ignore the loss of data integrity terms since they are overly dependent on numerous explicit previous regularization terms. In light of the aforementioned issues, this work suggests a dual-domain Jensen-Shannon divergence… More >

  • Open Access

    ARTICLE

    Object Tracking Algorithm Based on Multi-Time-Space Perception and Instance-Specific Proposals

    Jinping Sun*, Dan Li, Honglin Cheng

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 655-675, 2023, DOI:10.32604/iasc.2023.038016

    Abstract Aiming at the problem that a single correlation filter model is sensitive to complex scenes such as background interference and occlusion, a tracking algorithm based on multi-time-space perception and instancespecific proposals is proposed to optimize the mathematical model of the correlation filter (CF). Firstly, according to the consistency of the changes between the object frames and the filter frames, the mask matrix is introduced into the objective function of the filter, so as to extract the spatio-temporal information of the object with background awareness. Secondly, the object function of multi-feature fusion is constructed for the… More >

  • Open Access

    ARTICLE

    Visual Object Tracking Based on Modified LeNet-5 and RCCF

    Aparna Gullapelly, Barnali Gupta Banik*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1127-1139, 2023, DOI:10.32604/csse.2023.032904

    Abstract The field of object tracking has recently made significant progress. Particularly, the performance results in both deep learning and correlation filters, based trackers achieved effective tracking performance. Moreover, there are still some difficulties with object tracking for example illumination and deformation (DEF). The precision and accuracy of tracking algorithms suffer from the effects of such occurrences. For this situation, finding a solution is important. This research proposes a new tracking algorithm to handle this problem. The features are extracted by using Modified LeNet-5, and the precision and accuracy are improved by developing the Real-Time Cross-modality… More >

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