| \babel@toc {british}{}\relax | |
| \contentsline {chapter}{Resumo}{xi}{section*.1}% | |
| \contentsline {chapter}{\textit {Abstract}}{xiii}{section*.2}% | |
| \contentsline {chapter}{Agradecimentos}{xv}{chapter*.4}% | |
| \contentsline {chapter}{List of Tables}{xix}{section*.7}% | |
| \contentsline {chapter}{List of figures}{xix}{section*.8}% | |
| \contentsline {chapter}{List of abbreviations}{xxi}{chapter*.10}% | |
| \contentsline {chapter}{\numberline {1}Introduction}{1}{chapter.1}% | |
| \contentsline {section}{\numberline {1.1}Motivation}{2}{section.1.1}% | |
| \contentsline {section}{\numberline {1.2}Objectives}{4}{section.1.2}% | |
| \contentsline {section}{\numberline {1.3}Contributions}{5}{section.1.3}% | |
| \contentsline {section}{\numberline {1.4}Publications}{5}{section.1.4}% | |
| \contentsline {section}{\numberline {1.5}Document Structure}{6}{section.1.5}% | |
| \contentsline {chapter}{\numberline {2}Deep Learning for Computer Vision}{7}{chapter.2}% | |
| \contentsline {section}{\numberline {2.1}Architecture Basic Concepts}{8}{section.2.1}% | |
| \contentsline {section}{\numberline {2.2}Training Process}{12}{section.2.2}% | |
| \contentsline {section}{\numberline {2.3}Transfer Learning and Fine Tuning}{16}{section.2.3}% | |
| \contentsline {section}{\numberline {2.4}Deep Learning Architectures for Image Classification}{19}{section.2.4}% | |
| \contentsline {section}{\numberline {2.5}Deep Learning Architectures for Semantic Segmentation}{26}{section.2.5}% | |
| \contentsline {chapter}{\numberline {3}Explanable Aritificial Inteligence}{31}{chapter.3}% | |
| \contentsline {section}{\numberline {3.1}Local Interpretable Model-agnostic Explanations}{32}{section.3.1}% | |
| \contentsline {section}{\numberline {3.2}Gradient-weighted Class Activation Mapping}{34}{section.3.2}% | |
| \contentsline {chapter}{\numberline {4}Literature Review}{37}{chapter.4}% | |
| \contentsline {section}{\numberline {4.1}Deep Learning for Grapevine Classification}{38}{section.4.1}% | |
| \contentsline {section}{\numberline {4.2}Deep Learning for Grapevine Leaves Segmentation}{41}{section.4.2}% | |
| \contentsline {section}{\numberline {4.3}Discussion}{44}{section.4.3}% | |
| \contentsline {chapter}{\numberline {5}Methods}{47}{chapter.5}% | |
| \contentsline {section}{\numberline {5.1}Datasets}{48}{section.5.1}% | |
| \contentsline {section}{\numberline {5.2}Segmentation Experiments}{59}{section.5.2}% | |
| \contentsline {section}{\numberline {5.3}Classification Experiments}{62}{section.5.3}% | |
| \contentsline {chapter}{\numberline {6}Results and Discussions}{71}{chapter.6}% | |
| \contentsline {section}{\numberline {6.1}Segmentation}{71}{section.6.1}% | |
| \contentsline {section}{\numberline {6.2}Impact of Different Fine-Tuning Configurations}{75}{section.6.2}% | |
| \contentsline {section}{\numberline {6.3}Different Hyper-Parameters in the Grapevine Species Classification}{80}{section.6.3}% | |
| \contentsline {subsection}{\numberline {6.3.1}Impact of Using Focal Loss in the classification of the Unbalaced Dataset}{83}{subsection.6.3.1}% | |
| \contentsline {subsection}{\numberline {6.3.2}Segmentation as a Pre-processing Tool}{85}{subsection.6.3.2}% | |
| \contentsline {subsection}{\numberline {6.3.3}Different Architectures}{88}{subsection.6.3.3}% | |
| \contentsline {section}{\numberline {6.4}Discussion}{91}{section.6.4}% | |
| \contentsline {paragraph}{Overall Metrics.}{91}{paragraph*.11}% | |
| \contentsline {paragraph}{Fine-Tuning's Layer Configuration.}{92}{paragraph*.12}% | |
| \contentsline {paragraph}{Focal Loss.}{92}{paragraph*.13}% | |
| \contentsline {paragraph}{Segmentation.}{93}{paragraph*.14}% | |
| \contentsline {paragraph}{Different Architectures.}{93}{paragraph*.15}% | |
| \contentsline {chapter}{\numberline {7}Conclusions and Future work}{97}{chapter.7}% | |
| \contentsline {section}{\numberline {7.1}Conclusions}{97}{section.7.1}% | |
| \contentsline {section}{\numberline {7.2}Future Work}{99}{section.7.2}% | |