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Meng Wu and Pudong Shi
To address the problem of poor detection and under-utilization of the spatial relationship between nodes in human pose estimation, a method based on an improved spatial temporal graph convolutional network (ST-GCN) model is proposed. Firstly, upsampling ...
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Jong-Wook Kim, Jin-Young Choi, Eun-Ju Ha and Jae-Ho Choi
Seniors who live alone at home are at risk of falling and injuring themselves and, thus, may need a mobile robot that monitors and recognizes their poses automatically. Even though deep learning methods are actively evolving in this area, they have limit...
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Chih-Hung Wu, Te-Cheng Wu and Wen-Bin Lin
Originality/Contribution: The newly developed computer vision pose estimation technique in artificial intelligence (AI) is an emerging technology with potential advantages, such as high efficiency and contactless detection, for improving competitive adva...
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Shuwei Gan, Xiaohu Zhang, Sheng Zhuge, Chenghao Ning, Lijun Zhong and You Li
Space exploration missions involve significant participation from astronauts. Therefore, it is of great practical importance to assess the astronauts? performance via various parameters in the cramped and weightless space station. In this paper, we propo...
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Quan Sun, Xuhui Pan, Xiao Ling, Bo Wang, Qinghong Sheng, Jun Li, Zhijun Yan, Ke Yu and Jiasong Wang
In the realm of non-cooperative space security and on-orbit service, a significant challenge is accurately determining the pose of abandoned satellites using imaging sensors. Traditional methods for estimating the position of the target encounter problem...
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