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- W4324119115 abstract "In enclosed or extreme environments, the psychological stress and physical state of the operator can prevent the work from being carried out effectively in the long term. To decrease an operator’s decisional and operational errors caused by his poor status in this environment, it is significant to develop an assessment model for getting the operator’s working ability in order to assist operators in assisting decision-making or providing advice. The present study presents an assessment model for the operator’s working ability based on deep learning. The model recognizes the operator’s emotion by using the Vision Transformer (ViT) and then collects the operator’s physical state through smart devices. Obtaining the ability assessment results of personnel in different states through surveys. Eventually, assess his ability through the convolutional neural network (CNN). The result suggests that the proposed method is feasible and reliable. The assessment model proposed in this paper considering physical state and mental state can be used to assist decision-making and ability assessment." @default.
- W4324119115 created "2023-03-15" @default.
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- W4324119115 date "2022-11-25" @default.
- W4324119115 modified "2023-09-26" @default.
- W4324119115 title "Assessment model for operator’s working ability based on deep learning" @default.
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- W4324119115 doi "https://doi.org/10.1109/cac57257.2022.10054890" @default.
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