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Refinado por: Nome da Publicação: Automation In Construction remover assunto: Civil And Structural Engineering remover
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1
Automatic detection of hardhats worn by construction personnel: A deep learning approach and benchmark dataset
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Automatic detection of hardhats worn by construction personnel: A deep learning approach and benchmark dataset

Wu, Jixiu ; Cai, Nian ; Chen, Wenjie ; Wang, Huiheng ; Wang, Guotian

Automation in construction, 2019-10, Vol.106, p.102894, Article 102894 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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2
Image-based construction hazard avoidance system using augmented reality in wearable device
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Image-based construction hazard avoidance system using augmented reality in wearable device

Kim, Kinam ; Kim, Hongjo ; Kim, Hyoungkwan

Automation in construction, 2017-11, Vol.83, p.390-403 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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3
Towards a semantic Construction Digital Twin: Directions for future research
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Towards a semantic Construction Digital Twin: Directions for future research

Boje, Calin ; Guerriero, Annie ; Kubicki, Sylvain ; Rezgui, Yacine

Automation in construction, 2020-06, Vol.114, p.103179, Article 103179 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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4
Detecting non-hardhat-use by a deep learning method from far-field surveillance videos
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Detecting non-hardhat-use by a deep learning method from far-field surveillance videos

Fang, Qi ; Li, Heng ; Luo, Xiaochun ; Ding, Lieyun ; Luo, Hanbin ; Rose, Timothy M. ; An, Wangpeng

Automation in construction, 2018-01, Vol.85, p.1-9 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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5
Monitoring fatigue in construction workers using physiological measurements
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Monitoring fatigue in construction workers using physiological measurements

Aryal, Ashrant ; Ghahramani, Ali ; Becerik-Gerber, Burcin

Automation in construction, 2017-10, Vol.82, p.154-165 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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6
Transfer learning and deep convolutional neural networks for safety guardrail detection in 2D images
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Transfer learning and deep convolutional neural networks for safety guardrail detection in 2D images

Kolar, Zdenek ; Chen, Hainan ; Luo, Xiaowei

Automation in construction, 2018-05, Vol.89, p.58-70 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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7
The availability of wearable-device-based physical data for the measurement of construction workers' psychological status on site: From the perspective of safety management
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The availability of wearable-device-based physical data for the measurement of construction workers' psychological status on site: From the perspective of safety management

Guo, Hongling ; Yu, Yantao ; Xiang, Tian ; Li, Heng ; Zhang, Dan

Automation in construction, 2017-10, Vol.82, p.207-217 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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8
Evaluating the impact of mental fatigue on construction equipment operators' ability to detect hazards using wearable eye-tracking technology
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Evaluating the impact of mental fatigue on construction equipment operators' ability to detect hazards using wearable eye-tracking technology

Li, Jue ; Li, Heng ; Wang, Hongwei ; Umer, Waleed ; Fu, Hong ; Xing, Xuejiao

Automation in construction, 2019-09, Vol.105, p.102835, Article 102835 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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9
Identifying potential opportunities of building information modeling for construction and demolition waste management and minimization
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Identifying potential opportunities of building information modeling for construction and demolition waste management and minimization

Won, Jongsung ; Cheng, Jack C.P.

Automation in construction, 2017-07, Vol.79, p.3-18 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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10
Towards on-site hazards identification of improper use of personal protective equipment using deep learning-based geometric relationships and hierarchical scene graph
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Towards on-site hazards identification of improper use of personal protective equipment using deep learning-based geometric relationships and hierarchical scene graph

Chen, Shi ; Demachi, Kazuyuki

Automation in construction, 2021-05, Vol.125, p.103619, Article 103619 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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