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  • Open Access


    An Elevator Button Recognition Method Combining YOLOv5 and OCR

    Xinliang Tang1, Caixing Wang1, Jingfang Su1,*, Cecilia Taylor2

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 117-131, 2023, DOI:10.32604/cmc.2023.033327

    Abstract Fast recognition of elevator buttons is a key step for service robots to ride elevators automatically. Although there are some studies in this field, none of them can achieve real-time application due to problems such as recognition speed and algorithm complexity. Elevator button recognition is a comprehensive problem. Not only does it need to detect the position of multiple buttons at the same time, but also needs to accurately identify the characters on each button. The latest version 5 of you only look once algorithm (YOLOv5) has the fastest reasoning speed and can be used for detecting multiple objects in… More >

  • Open Access


    Moving Multi-Object Detection and Tracking Using MRNN and PS-KM Models

    V. Premanand*, Dhananjay Kumar

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1807-1821, 2023, DOI:10.32604/csse.2023.026742

    Abstract On grounds of the advent of real-time applications, like autonomous driving, visual surveillance, and sports analysis, there is an augmenting focus of attention towards Multiple-Object Tracking (MOT). The tracking-by-detection paradigm, a commonly utilized approach, connects the existing recognition hypotheses to the formerly assessed object trajectories by comparing the similarities of the appearance or the motion between them. For an efficient detection and tracking of the numerous objects in a complex environment, a Pearson Similarity-centred Kuhn-Munkres (PS-KM) algorithm was proposed in the present study. In this light, the input videos were, initially, gathered from the MOT dataset and converted into frames.… More >

  • Open Access


    Multi-Object Detection of Chinese License Plate in Complex Scenes

    Dan Liu1,3, Yajuan Wu1, Yuxin He2, Lu Qin2, Bochuan Zheng2,3,*

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 145-156, 2021, DOI:10.32604/csse.2021.014646

    Abstract Multi-license plate detection in complex scenes is still a challenging task because of multiple vehicle license plates with different sizes and classes in the images having complex background. The edge features of high-density distribution and the high curvature features of stroke turning of Chinese character are important signs to distinguish Chinese license plate from other objects. To accurately detect multiple vehicle license plates with different sizes and classes in complex scenes, a multi-object detection of Chinese license plate method based on improved YOLOv3 network was proposed in this research. The improvements include replacing the residual block of the YOLOv3 backbone… More >

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