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Cited by 70 publications
(12 citation statements)
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“…The momentum of the optimizer and weight decay was set to 0.937 and 5e-4 respectively. Figure 3 For visual verification, this study used the publicly available dataset of Moving Objects in Construction Sites (MOCS) (Xuehui et al, 2021). This dataset contains 41,668 images of 13 categories of construction mobile objects.…”
Section: Experimental Details and Resultsmentioning
confidence: 99%
“…The momentum of the optimizer and weight decay was set to 0.937 and 5e-4 respectively. Figure 3 For visual verification, this study used the publicly available dataset of Moving Objects in Construction Sites (MOCS) (Xuehui et al, 2021). This dataset contains 41,668 images of 13 categories of construction mobile objects.…”
Section: Experimental Details and Resultsmentioning
confidence: 99%
“…Additionally, this study offers valuable information about research themes published on the topic of deep learning and its implementation in the construction industry through cluster analysis and critical review. Despite the contributions offered, the (Bang et al 2019, Chen et al 2020, Guo et al 2020, Slaton et al 2020, Xuehui et al 2021, Zhou et al 2021b, Lin et al 2021, Sim et al 2021 (Olanrewaju et al 2020, Kamal et al 2020, Liu et al 2020, Scarpiniti et al 2021)…”
Section: Discussionmentioning
confidence: 99%
“…Another reason is that the algorithms are often benchmarked on the number of identified hazards but not compared to the number of existing hazards. Benchmarking is commonly used in other domains such as machine learning and computer vision, where a portion of the data, i.e., test data, is used as ground truth to assess the correctness and soundness of a trained model (Deng et al, 2009;Xuehui et al, 2021). The adoption of benchmarking provides the stakeholders with a deeper insight into the quality of the hazard identification provided.…”
Section: Construction Hazard Identificationmentioning
confidence: 99%