Mask Wearing Detection Based on Deep Learning

声明

Abstract

摘要

Acknowledgments

Table of Contents

List of Figures

List of Tables

Chapter 1 Introduction

1．1 Research Background and Significance

1．2Related Work

1．2．1Status of Object Detection

1．2．2Status of Classification Network

1．3Main Research Content of Thesis

1．4 Chapter Arrangement

Chapter 2 Data Set and Experimental Environment

2．1 Establishment of Mask Data Set

2．2 Enhanced Processing of Mask Data Set

2．3 The Experimental Environment

2．4 Summary of Chapter

Chapter 3 Mask Wearing Detection Based on The Optimized YOLOv4 Model

3．1 Overview of Object Detection Networks

3．1．1 Faster R-CNN

3．1．2 SSD

3．1．3YOLOv4

3．2 Mask Wearing Detection Based on The Optimized YOLOv4 Algorithm

3．2．1 The Original YOLOv4 Algorithm

3．2．2 The Optimized YOLOv4 Algorithm

3．3 Experimental Results and Analysis

3．3．1 Experimental Evaluation Criteria

3．3．2 Experimental Results

3．3．3 Analysis of Experimental Results

3．4 Summary of Chapter

Chapter 4 Mask Wearing Detection Based on The Hybrid Model

4．1 Overview of Classification Networks

4．1．1 VGG16

4．1．2 ResNet

4．1．3 MobileNetV2

4．2 The Hybrid Model Algorithm

4．3 Experimental Results and Analysis

4．3．1 Experimental Results

4．3．2 Analysis of Experimental Results

4．4 Summary of Chapter

Chapter 5 Conclusion and Future Work

5．1 Conclusion

5．2 Future Work

References