Deep Learning Model Design of Video Target Tracking Based on TensorFlow Platform

Fan, 刘帆 Liu; Pengyuan, 刘鹏远 Liu; Bing, 李兵 Li; Binbin, 徐彬彬 Xu

doi:10.3788/lop54.091501

激光与光电子学进展

2017

DOI: 10.3788/lop54.091501

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Deep Learning Model Design of Video Target Tracking Based on TensorFlow Platform

刘帆 Liu Fan¹,

刘鹏远 Liu Pengyuan²,

李兵 Li Bing³

et al.

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Research on Care Workers Physical Exercise Video Tracking based on Deep Neural Network

Yanli

2022

International Journal of Circuits, Systems and Signal Processing

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Most nursing workers have a positive cognitive attitude towards physical exercise, but their exercise behavior lags behind. There are significant differences in the frequency, time, experience and load of physical exercise among nurses of different ages. Care workers’ union organizations should try their best to provide health assistance to medical staff to meet their needs for physical exercise, so as to ensure their physical and mental health. Aiming at the problem of target tracking in motion video, this paper proposes a method of tracking motion video of nursing staff based on deep neural network (DNN). The effectiveness and adaptability of this method are verified by an example. This method can not only track and estimate the position of the target effectively, but also describe the shape of the target well, thus solving the problem that the shape of the target is complex and difficult to track in motion video.

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Research on Care Workers Physical Exercise Video Tracking based on Deep Neural Network

Yanli

2022

International Journal of Circuits, Systems and Signal Processing

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show abstract

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Deep Learning Model Design of Video Target Tracking Based on TensorFlow Platform

Cited by 1 publication

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Research on Care Workers Physical Exercise Video Tracking based on Deep Neural Network

Research on Care Workers Physical Exercise Video Tracking based on Deep Neural Network

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