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研究生:季信瑋
研究生(外文):CHI, HSIN-WEI
論文名稱:應用深度學習進行光譜辨析搭配雲端光譜分析平台建置
論文名稱(外文):Classification of Spectrum Using Deep Neural Network and Cloud Spectrum Service Development
指導教授:張正春張正春引用關係
指導教授(外文):CHANG, CHENG-CHUN
口試委員:邵皓強高立人
口試委員(外文):SHAO, HAO-CHIANGKAU, LIH-JEN
口試日期:2020-05-27
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電機工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:118
中文關鍵詞:光譜訊號轉換光譜辨識開放式AI平台
外文關鍵詞:Spectrum transformSpectrum classificationCloud AI Service
相關次數:
  • 被引用被引用:0
  • 點閱點閱:181
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
摘要 i
Abstract ii
誌謝 iii
目錄 iv
表目錄 vii
圖目錄 ix
第一章 緒論 1
1.1 前言 1
1.2 研究動機與方法 2
1.3 論文架構 3
第二章 背景知識 4
2.1 雲端運算 4
2.2 人工智慧 7
2.3 光譜感測 9
第三章 研究方法 10
3.1 資料前處理 11
3.1.1. 格拉姆角場(Gramin Agular Field, GAF) 11
3.1.2. 馬可夫轉換場(Markov Transition Field, MTF) 14
3.1.3. 遞迴圖(Recurence Plots, RP) 15
3.1.4. 經驗模態分析(Empirical Mode Decomposition, EMD) 16
3.1.5. 希爾伯特-黃轉換搭配格拉姆角場(Hilbert-Huang Transform with GAF) 20
3.2 影像辨析模型 24
3.2.1. 卷積神經網路 24
3.2.2. LeNet-5 27
3.2.3. 深度殘差網路 31
第四章 雲端平台架設 34
4.1 基礎伺服器架設 35
4.1.1. DNS伺服器 35
4.1.2. 郵件伺服器 40
4.1.3. 網頁伺服器 50
4.1.4. 資料庫伺服器 56
4.1.5. 廣播伺服器 59
4.1.6. 預測伺服器 61
4.2 Amazon SageMaker服務 65
4.2.1. Amazon SageMaker 模型訓練功能 65
4.2.2. Amazon SageMaker訓練流程 67
4.3 平台整合與細部設定 71
4.3.1. 伺服器硬體相關設定 71
4.3.2. Laravel及相關伺服器細部設定 74
4.3.3. 平台架構與運作流程 79
4.4 雲端光譜分析平台成品 89
第五章 實驗與結果 95
5.1 實驗前置作業 96
5.1.1. 光譜感測模組 96
5.1.2. 實驗一之色採校正板與量測應用程式 97
5.1.3. 實驗三與實驗四之PPG訊號與量測應用程式 98
5.1.4. 前處理相關參數設定 99
5.1.5. 神經網路模型相關參數設定 99
5.2 實驗一、色彩校準盤之色彩光譜分類 100
5.3 實驗二、皮膚色彩分類 103
5.4 實驗三、PPG訊號辨識 104
5.5 實驗四、PPG訊號血壓預測 107
5.6 實驗結果探討 108
第六章 結論與未來發展 109
6.1 結論 109
6.2 未來發展 110
參考文獻 111

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