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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭彥甫(Yan-Fu Kuo) | |
| dc.contributor.author | Tsan-Yu Wu | en |
| dc.contributor.author | 吳璨妤 | zh_TW |
| dc.date.accessioned | 2021-06-17T02:14:00Z | - |
| dc.date.available | 2020-08-21 | |
| dc.date.copyright | 2020-08-21 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-08-18 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68172 | - |
| dc.description.abstract | 森林是陸域生態系重要的一環，不但孕育豐富的動植物，更能提供木材、調節氣候，對人類社會與環境帶來諸多效益。為了更有效率應用及管理這些資源，準確的物種辨識是不可或缺的步驟。殼斗科與樟科是台灣中低海拔的優勢樹種，因為台灣豐富的地形與氣候變化分化出許多台灣特有種。現今的植物物種辨識依靠比對遺傳標記的相似性，然而該方法昂貴並耗時。近年來卷積神經網路 (convolutional neural networks, CNNs) 廣泛被應用於各種複雜的機器視覺任務。因此本研究利用深度卷積神經網路自動辨識35種殼斗科與樟科物種，其中葉片影像由彩色平板掃描機所取得。本研究之自動辨識模型使用三種不同的深度卷積神經網路架構，包含：DenseNet-121、MobileNet V2與Xception。研究中卷積神經網路模型之準確率最高可達99.396%，而在圖像顯示卡 (Graphics Processing Unit, GPU) 最快之辨識速度可達17.1毫秒∕影像。 | zh_TW |
| dc.description.abstract | Forests contain abundant resources and provide benefits to human societies, such as edible fruits, medicinal substances, and woods for construction. Species identification is an essential step for the management and utilization of the resources. Nowadays, the species identification relies on the examining the similarity of genetic markers. The approach is, however, time consuming, laborious, and costly. Fagaceae and Lauraceae are two woody plant families with high species richness that dominate the low and middle altitude regions in Taiwan. This paper proposed a machine vision approach for identifying the species of families Fagaceae and Lauraceae using leaf images. Leaf specimens of 35 Fagaceae and Lauraceae species were collected. The images of the leaves were acquired using flatbed scanners. Deep convolutional neural networks (DCNN) of three architectures, namely DenseNet-121, MobileNet V2, and Xception, were next trained to identify the species. Among all, Xception reached the highest mean accuracy of 99.396%, and MobileNetV2 required the least mean test time of 17.1 ms per image using an GPU. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T02:14:00Z (GMT). No. of bitstreams: 1 U0001-1708202015491400.pdf: 1961644 bytes, checksum: 682d1493492aa21876830b16302f3719 (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | ACKNOWLEDGEMENTS i 摘要 ii ABSTRACT iii TABLE OF CONTENTS iv LIST OF FIGURES vi LIST OF TABLES vii CHAPTER 1. INTRODUCTION 1 1.1 Background 1 1.2 Objectives 3 1.3 Organization 3 CHAPTER 2. LITERATURE REVIEW 4 2.1 Conventional Molecular-marker-based approaches 4 2.2 Image-based and machine learning approaches 4 2.3 CNN-based approaches for plant species identification 5 CHAPTER 3. MATERIALS AND METHODS 6 3.1 Leaf sample collection and image acquisition 6 3.2 Leaf segmentation 7 3.3 Image augmentation and normalization 8 3.4 CNN models and training details 9 3.5 Visualization of the CNN models 10 3.6 Pruning of the CNN models 10 CHAPTER 4. RESULTS AND DISSCUSSION 12 4.1 The performance of leaf segmentation model 12 4.2 The convergence of the species identification models 12 4.3 The performance of the trained models 13 4.4 Saliency maps and Grad-CAMs of the trained models 17 4.5 Pruning of the trained models and parameter redundancy 21 CHAPTER 5. CONCLUSIONS 23 REFERENCES 24 | |
| dc.language.iso | en | |
| dc.subject | 深度學習 | zh_TW |
| dc.subject | 卷積神經網路 | zh_TW |
| dc.subject | 植物物種辨識 | zh_TW |
| dc.subject | 樟科 | zh_TW |
| dc.subject | 殼斗科 | zh_TW |
| dc.subject | Deep learning | en |
| dc.subject | Convolutional neural network | en |
| dc.subject | Lauraceae | en |
| dc.subject | Plant identification | en |
| dc.subject | Fagaceae | en |
| dc.title | 利用葉片影像與卷積神經網路辨識殼斗科與樟科之物種 | zh_TW |
| dc.title | Identifying Fagaceae and Lauraceae species using leaf images and convolutional neural networks | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 花凱龍(Kai-Lung Hua),鄭文皇(Wen-Huang Cheng),楊智凱(Chih-Kai Yang) | |
| dc.subject.keyword | 卷積神經網路,深度學習,殼斗科,樟科,植物物種辨識, | zh_TW |
| dc.subject.keyword | Convolutional neural network,Deep learning,Fagaceae,Lauraceae,Plant identification, | en |
| dc.relation.page | 28 | |
| dc.identifier.doi | 10.6342/NTU202003782 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-08-19 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 生物機電工程學系 | zh_TW |
| 顯示於系所單位： | 生物機電工程學系 | |
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