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研究生: 單開民
Shan, Kai-Min
論文名稱: 在小樣本情境下增強生成對抗網路之判別網路的訓練效果
Improve the training effectiveness of the discriminating network of the generated adversarial network in the context of small samples
指導教授: 利德江
Li, Der-Chiang
學位類別: 碩士
Master
系所名稱: 管理學院 - 資訊管理研究所
Institute of Information Management
論文出版年: 2021
畢業學年度: 109
語文別: 中文
論文頁數: 48
中文關鍵詞: 小樣本虛擬樣本產生生成對抗網路
外文關鍵詞: small data set, virtual sample generation, Generative Adversarial Network
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  • 摘要 i 目錄 xx 圖目錄 xxii 表目錄 xxiii 第一章 緒論 1 1.1 研究背景 1 1.2 研究動機 3 1.3 研究目的 5 1.4 研究限制 5 1.5 研究架構 5 第二章 文獻回顧 8 2.1 生成對抗網路之回顧 8 2.1.1 生成對抗網路 8 2.2 虛擬樣本學習方法 12 2.2.1 資訊擴散技術 12 2.3 支援向量機 18 2.4 決策樹 21 第三章 研究方法 23 3.1 符號定義 23 3.2 虛擬樣本生成 23 3.2.1 MTD值域推估 24 3.2.2 MTD樣本生成 25 3.3 生成對抗網路架構 27 3.4 研究方法與流程 28 第四章 實證研究 29 4.1 實驗環境 29 4.1.1 實驗方式 29 4.1.2 假設檢定 30 4.1.3 預熱學習率 30 4.1.4 實驗資料 31 4.1.5 分類預測模型 32 4.1.6 程式語言與執行環境 32 4.2 實驗結果 33 4.2.1 Wine資料集結果 33 4.2.2 Seeds資料集結果 37 4.2.3 小結 41 第五章 結論與建議 42 5.1 結論 42 5.2 未來研究建議 42 參考文獻 44

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