The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem

碩士 === 國立中央大學 === 數學系 === 107 === The purpose of this thesis is to explore the training resul ts of two deep learning models ：(1) Support Vector Machine ；(2) Softmax Classifier in image recognition, and study the influence of loss functions on the iterative parameters . We demonstrate the results of...

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Main Authors:	Kuan-Ting Chen, 陳冠廷
Other Authors:	Meng-Kai Hong
Format:	Others
Language:	zh-TW
Published:	2018
Online Access:	http://ndltd.ncl.edu.tw/handle/93g7ka

id	ndltd-TW-107NCU05479002
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spelling	ndltd-TW-107NCU054790022019-06-01T03:42:08Z http://ndltd.ncl.edu.tw/handle/93g7ka The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem SVM(支持向量機)與Softmax在蝴蝶辨識問題中之觀察比較 Kuan-Ting Chen 陳冠廷碩士國立中央大學數學系 107 The purpose of this thesis is to explore the training resul ts of two deep learning models ：(1) Support Vector Machine ；(2) Softmax Classifier in image recognition, and study the influence of loss functions on the iterative parameters . We demonstrate the results of these two models by use of the image s of butterflies. There are five types of butterflies with 8214 pictures obtained through the onlin e database website. We use these pictures for the files of data samples to two deep learning models, and observe the training time and accuracy. Next, we analyze the fitting situation to the itera tive results. Finally, we give the reason s why the performan ce of these two models are not ideal. Therefore, we are able to improve the performance by fixing the datasets . Meng-Kai Hong 洪盟凱 2018 學位論文 ; thesis 65 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 國立中央大學 === 數學系 === 107 === The purpose of this thesis is to explore the training resul ts of two deep learning models ：(1) Support Vector Machine ；(2) Softmax Classifier in image recognition, and study the influence of loss functions on the iterative parameters . We demonstrate the results of these two models by use of the image s of butterflies. There are five types of butterflies with 8214 pictures obtained through the onlin e database website. We use these pictures for the files of data samples to two deep learning models, and observe the training time and accuracy. Next, we analyze the fitting situation to the itera tive results. Finally, we give the reason s why the performan ce of these two models are not ideal. Therefore, we are able to improve the performance by fixing the datasets .
author2	Meng-Kai Hong
author_facet	Meng-Kai Hong Kuan-Ting Chen 陳冠廷
author	Kuan-Ting Chen 陳冠廷
spellingShingle	Kuan-Ting Chen 陳冠廷 The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem
author_sort	Kuan-Ting Chen
title	The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem
title_short	The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem
title_full	The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem
title_fullStr	The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem
title_full_unstemmed	The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem
title_sort	comparison of support vector machine and softmax classifier in butterflies recognition problem
publishDate	2018
url	http://ndltd.ncl.edu.tw/handle/93g7ka
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The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem

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