بانک مقالات

روش مبتنی بر یادگیری عمیق برای شناسایی کارهای تایید نشده در سایت های ساختمانی

A deep learning-based method for detecting non-certified work on construction sites

سال انتشار : 2018

تعداد صفحه : 13

کلیدواژه ها:  Construction safety, Certification checking, Trade recognition, Identification, Deep learning

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ABSTRACT

For the design of large infrastructure projects such as inner-city subway tracks, it proves necessary to consider differing model scales, ranging from the scale of several kilometers down to a few millimeters. This challenge can be addressed by using multi scale product models comprising multiple levels of detail (LoD). Ensuring consistency across the different LoDs can be achieved by applying procedural and parametric modeling techniques while creating the model. This results in a flexible multi-scale model that can be easily modified on one scale while other scales are automatically updated. However, the correct application of parametric constraints and procedural dependencies has shown to be a very complex and timeconsuming process. To address this issue, this papers presents a semi-automated detailing mechanism, which is based on formal procedures based on graphs and graph transformations. This paper discusses how procedural parametric models based on two-dimensional sketches can be represented by graphs and how detailing steps in the form of parametric modeling operations can be formalized by using rule-based graph rewriting



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مجلات و ژورنال های بین المللی

Elsevier

ترجمه

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رایگان

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