Engaging Safety Professionals in Electrical Safety Topics: A Survey of Decision-Making Processes, Best Practices, and Industry Challenges

Bugaris, Rachel M.; Floyd, H. Landis

doi:10.1109/mias.2020.3024488

Cited by 1 publication

(2 citation statements)

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“…The image of the Mish function is shown in Equation (10). As can be seen from the figure, the Mish function is unbounded above and bounded below, and the curve is smooth and nonmonotonic, which are all conducive to improving the model training results.…”

Section: ( )mentioning

confidence: 99%

“…Mobile inspection robots are equipped with high-definition cameras to obtain real-time data of the power construction site and are based on high-precision machine vision technology to form an intelligent analysis algorithm. When a power operator is found to have illegal actions, it can be reflected in the control center in real-time [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Research on Electricity Operation Behaviour Recognition Strategy Combined with Intelligent Image Recognition and Its Key Technology

Feng,

Chen,

Zhou

et al. 2024

Applied Mathematics and Nonlinear Sciences

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This paper builds a power operation target detection model based on the YOLOv4 algorithm in intelligent image recognition, and optimizes the YOLOv4 algorithm by combining with the loss function to improve the accuracy of power target operation detection. The kmeans++ algorithm was used to cluster the electric power operation behaviors to obtain a more accurate electric power operation behavior dataset. Three sets of tests were conducted after the model was constructed, targeting the behavioral set of electric power workers in a certain place and the behavior in VOC format, followed by the multi-target tracking effect test. The analysis based on the obtained data showed that the helmet placement detection confidence, fatigue detection confidence, smoking detection confidence, and fall detection confidence reached 0.97, 0.93, 0.89, and 0.93, respectively. The transmission speed got 53.58 fps, and the recall and precision of the multi-target tracking were also above 93%. The YOLOv4 detection model based on keans++ clustering algorithm can effectively detect and identify the variable power operation behavior images.

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confidence: 99%

Section: Introductionmentioning

confidence: 99%