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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/82692

    Title: 市區道路鋪面破壞導入人工智慧之應用;Research on the Application of AI Artificial Intelligence in Urban Road Damage Analysis
    Authors: 羅學韓;LO, HSUEH-HAN
    Contributors: 土木工程學系在職專班
    Keywords: 深度學習;影像辨識;市區道路;道路巡查;鋪面狀況指標;Deep Learning;Image recognition;Urban road;Road inspection;Pavement Condition Index (PCI)
    Date: 2020-01-21
    Issue Date: 2020-06-05 16:29:33 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 台灣地區在各道路主管機關之調查作業上仍採用過去傳統的調查方
    式,於車輛上採目視方式尋找破壞再進行人工量測,並在19 種常見的道
    破壞需養護之問題加以探討,以及作為即時性派工之應用。;In Taiwan, the traditional survey methods are still used in the survey
    operations of various road authorities. The vehicles are visually searched for
    damage and then manually measured. Of the 19 common road damage factors,
    there are often causes for misdiagnosis by field engineers. Generation, this method
    is not only time-consuming and labor-intensive, but also consumes too much
    operation time on the overall paving maintenance operation. This study collects
    damage patterns such as provincial roads, expressways, urban roads, county and
    rural roads, and national highways to carry out depth Learn image recognition. In
    the hardware selection and software design, the device is installed on the road
    inspection vehicle, the road image is captured by the camera lens, the photo is
    uploaded to the cloud through the network, and the cloud automatically performs
    image analysis to identify road damage It also interprets and analyzes roads and
    applications to facilitate the collection of a large number of paving data and reduce
    the cost of manufacturers and the consumption of human resources. Finally,
    through the inspection mechanism to find out the problems that need to be
    maintained and explore, and its application as an immediate dispatch.
    Appears in Collections:[土木工程學系碩士在職專班] 博碩士論文

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