| Academic Year |
2025Year |
School/Graduate School |
Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Informatics and Data Science Program |
| Lecture Code |
WSN23201 |
Subject Classification |
Specialized Education |
| Subject Name |
AIOps演習C（自動運転系） |
Subject Name
（Katakana） |
エーアイオプスエンシュウシー（ジドウウンテンケイ） |
Subject Name in
English |
AIOps Lab C |
| Instructor |
GU YANLEI |
Instructor
(Katakana) |
コ エンライ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, First Semester, Intensive |
| Days, Periods, and Classrooms |
(Int) Inte |
| Lesson Style |
Seminar |
Lesson Style
(More Details) |
Face-to-face |
| This is a lab-based class held in person. |
| Credits |
1.0 |
Class Hours/Week |
|
Language of Instruction |
E
:
English |
| Course Level |
7
:
Graduate Special Studies
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
02
:
Information Science |
| Eligible Students |
Graduate students who have registered for the AIOps engineer training program |
| Keywords |
Python, OpenCV, Computer Vision, Sensor Fusion |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Class Objectives
/Class Outline |
This course aims to equip students with practical skills and knowledge in autonomous driving related technologies.
Through hands-on labs and targeted tutorials, students will learn essential techniques including object detection, stereo vision, and sensor fusion. |
| Class Schedule |
Lesson 1: Introduction to Autonomous Driving and OpenCV
Lesson 2: Object Detection for Autonomous Driving (1)
Lesson 3: Object Detection for Autonomous Driving (2)
Lesson 4: Stereo Camera Systems for Autonomous Driving (1)
Lesson 5: Stereo Camera Systems for Autonomous Driving (2)
Lesson 6: Sensor Fusion for Autonomous Driving (1)
Lesson 7: Sensor Fusion for Autonomous Driving (2)
Lesson 8: Final Project
Project Assignments and Tests |
Text/Reference
Books,etc. |
OpenCV Documentation: OpenCV-Python Tutorials |
PC or AV used in
Class,etc. |
Handouts, Microsoft Teams, moodle |
| (More Details) |
|
| Learning techniques to be incorporated |
Discussions, PBL (Problem-based Learning)/ TBL (Team-based Learning), Project Learning, Post-class Report |
Suggestions on
Preparation and
Review |
Review basics of Python and OpenCV (a certain maturity in using Python/Numpy is expected). |
| Requirements |
*Students who wish to take AIOps Lab C are advised to take AIOps Lab A first. |
| Grading Method |
Evaluation will be based on the assignment projects and tests. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
*The course will be conducted over four days, from September 16th, 2025 (Tuesday) to September 19th, 2025 (Friday).
*Lessons will be held each day from Period 1 to Period 4 (from 8:45 to 12:00). |
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |