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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/79636

    Title: 影像模糊方法在蝴蝶辨識神經網路中之應用;Application of Image Blurring Method in Butterfly Identification Neural Network
    Authors: 李政瑜;Lee, Cheng-Yu
    Contributors: 數學系
    Keywords: 神經網路
    Date: 2018-10-30
    Issue Date: 2019-04-02 15:09:35 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 本研究旨在探討深度學習模型”多層感知神經網路”及”卷積神經網路”在圖像辨識上的訓練結果比較,也研讀當今常用的優化算法,熟知損失函數對參數更新的影響關係,兩個模型訓練將以蝴蝶圖片進行實作。
    ;The goal of this thesis is to explore the training results of two deep learning models "multilayer perceptual neural network" and "convolution neural network" in image recognition, and study the popular optimization algorithms. To this topic, we study the influence of loss functions on iterative parameters, and demonstrate two models with the pictures of butterflies.
    There are five types of butterflies with 9141 pictures obtained through the online database website. We use these pictures for the files of data samples to two deep learning models, and observe the training time and accuracy by establishing the hidden layers. Then, we analyze the fitting situation to the iterative results. Finally, by using principle component analysis(PCA) in dimension reduction method, we preprocess the data and observe the reduction effect of the image background so that we can improve the training or verification accuracy.
    Appears in Collections:[數學研究所] 博碩士論文

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