English  |  正體中文  |  简体中文  |  Items with full text/Total items : 75369/75369 (100%)
Visitors : 25466838      Online Users : 368
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version

    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/89768

    Title: 花樣口罩辨識;The patterned face mask detection
    Authors: 姜亭光;Jiang, Ting-Guang
    Contributors: 資訊工程學系在職專班
    Keywords: 影像辨識;人臉偵測;深度學習;口罩辨識;Image recognition;Face detection;Deep learning;Mask detection
    Date: 2022-09-16
    Issue Date: 2022-10-04 11:58:48 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 由於2019年冠狀病毒COVID-19的迅速傳播,已影響了全世界,各國政府與人民正面臨著健康危機,COVID-19是一種呼吸系統疾病,可導致受影響個體出現嚴重的肺炎病例。這種疾病是通過與感染者的直接接觸,以及當感染者咳嗽、打噴嚏或將病毒呼出到空氣中時釋放的唾液珠、呼吸道飛沫而獲得的,因此世界衛生組織WHO提出建議,人們戴口罩在預防COVID-19傳播方面非常有效。


    ;In 2019, governments and people around the world were facing health
    issues due to the rapid spread of the coronavirus, a respiratory
    disease that causes severe pneumonia. COVID-19 transmits when people
    breathe in air contaminated by droplets and small airborne particles
    containing the virus, so the World Health Organization (WHO) recommends
    people wear masks to prevent the spread of COVID-19.

    In recent years, with development of artificial intelligence and
    computer imaging technology, the face mask-wearing detection algorithm
    automatically detects masks which can decrease the waste of human
    resources and creates alert which can reduce the spread of the disease.

    The current method used in mask detection has low accuracy when
    people wearing masks with patterns or dark-colored. Therefore, in this
    study, improvement will be proposed in order to increase accuracy.

    The goal of this research is to propose several mask detection methods by using the deep learning algorithm combined with the image processing algorithm. First, the face part in the image is extracted by the face recognition classifier, and then use the pre-trained CNN model as a basis to gradually improve its model network structure.

    According to the experiment, the accuracy rate reaches 95%, which
    proves that this method has a certain degree of accuracy after optimization.
    Appears in Collections:[資訊工程學系碩士在職專班 ] 博碩士論文

    Files in This Item:

    File Description SizeFormat

    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明