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研究生: 邱千泰
CHIU, CHIEN-TAI
論文名稱: 印刷業數位轉型:以燙金錯誤偵測為例
The Digital Transformation In The Printing Industry: Take Hot Foil Stamping Defects Recognition As An Example
指導教授: 謝明華
口試委員: 李宜熹
邱于芬
學位類別: 碩士
Master
系所名稱: 商學院 - 經營管理碩士學程(EMBA)
Executive Master of Business Administration(EMBA)
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 51
中文關鍵詞: 數位轉型卷積神經網路模型印刷業
DOI URL: http://doi.org/10.6814/NCCU202200322
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  • 在本文章中,探討了現今印刷業所面臨的挑戰,包含了消費習慣改變導致印刷需求下降等等。這些挑戰迫使著印刷業進行數位轉型。其中藉由光學儀器與機器學習辨識印刷及燙金錯誤成為了一個可能的轉型方向,可以降低人力成本的花費,同時也能幫助減少管理問題。在數位轉型的方法中,以機器學習作為數位轉型的工具成為了常見的數位轉型方法。在這些機器學習方法中,卷積神經網路是較為適合用於圖像辨識的模型,也能夠用於各種分類問題上。本文以燙金業為例,探討卷積神經網路應用於燙金錯誤辨識所面臨的議題。


    摘要 1
    目錄 1
    第一章 國際印刷業數位轉型發展態勢 2
    第二章 數位轉型文獻探討 8
    第三章 機器學習介紹 15
    第一節 人工智慧與機器學習 15
    第二節 機器學習的類型 16
    第四章 以燙金錯誤偵測探討機器學習的應用 21
    第一節 卷積神經網路模型 21
    第二節 將卷積神經網路模型應用於燙金錯誤辨識 34
    第五章 結論及展望 48
    參考文獻 50

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