使用深度学习进行目标检测

Introduction

Familiarize yourself with concepts covered in the course.

课程：

Course Overview

Learning Outcomes

Course Example and Prerequisite Concepts

Pretrained YOLOX Detectors

Prepare Data for Transfer Learning

Prepare ground truth data for transfer learning and split labeled data into training, validation, and test sets.

课程：

Label Ground Truth Data with the Image Labeler App

Ground Truth Data

Split Data into Training, Validation, and Testing Data

Train and Use a Detector

Define training options. Train and use a YOLOX object detector to find custom classes.

课程：

Define Training Options

Train a Detector

Detect Objects Using a Trained Detector

Evaluate an Object Detector

Evaluate the quality of an object detector by calculating the confusion matrix and precision-recall curves.

课程：

What Does It Mean for a Detection to Be Right or Wrong?

Measure the Correctness of a Bounding Box Location

Calculate the Confusion Matrix

What Are Precision and Recall Curves?

Plot Precision and Recall Curves

Select Detection Score Threshold Based on Precision-Recall Curves

Data Augmentation

Incorporate data augmentation into an object detection model.

课程：

What Is Data Augmentation?

Data Augmentation for the ASL Example

Augment Images and Bounding Boxes

Create a Data Augmentation Function

Transform Ground Truth Data with Data Augmentation

Evaluate the Effectiveness of Augmentation

Conclusion

Learn next steps and give feedback on the course.

课程：

Summary

Additional Resources

Survey

课程模块

Introduction

Prepare Data for Transfer Learning

Train and Use a Detector

Evaluate an Object Detector

Data Augmentation

Conclusion

语言

带自动反馈的实操练习
通过 Web 浏览器访问 MATLAB
可共享的进度报告和课程证书

计算机视觉入门之旅

深度学习入门之旅

使用深度学习进行目标检测

课程模块

Introduction

Prepare Data for Transfer Learning

Train and Use a Detector

Evaluate an Object Detector

Data Augmentation

Conclusion

语言

带自动反馈的实操练习通过 Web 浏览器访问 MATLAB可共享的进度报告和课程证书

计算机视觉入门之旅

深度学习入门之旅

带自动反馈的实操练习
通过 Web 浏览器访问 MATLAB
可共享的进度报告和课程证书