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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Undergraduate major in Systems and Control Engineering
- Instructor(s)
- Tanaka Masayuki Nakadai Kazuhiro
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- -
- Group
- -
- Course number
- SCE.M351
- Credits
- 1
- Academic year
- 2024
- Offered quarter
- 4Q
- Syllabus updated
- 2024/4/11
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
With the recent development of machine learning, the framework of sensing has been expanding. Students will learn the principles of various sensors used in such sensing and the measurement information systems based on the sensors. Students will also deepen their understanding of advanced sensing systems used in social infrastructure and automobiles.
Student learning outcomes
Understand principle of fundamental sensors and their applications. Acquirement of knowledge on advanced system structure.
Course taught by instructors with work experience
| ✔ Applicable | How instructors' work experience benefits the course |
|---|---|
| In this lecture, teachers with research experiences teach the basic concept which can be applied to new technology changing every day. |
Keywords
Principle of sensors, measurement information systems, social infrastructure
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Class flow
Omnibus lecture by part-time lecturers
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | About this lecture. What is "sensor"? | Understand necessity of this lecture. |
| Class 2 | Visual processing and sensing(1) | Understand the fundamentals of sensing technology for image processing. |
| Class 3 | Visual processing and sensing(2) | Understand the application of image processing to measurement information systems. |
| Class 4 | Multimodal scene recognition and sensing(1) | Understand the fundamentals of sensing technology for multimodal scene recognition. |
| Class 5 | Multimodal scene recognition and sensing(2) | Understand the application of sensing technology for multimodal scene recognition. |
| Class 6 | Generative AI and LLM(1) | Understand the fundamentals of generative AI and large-scale language models. |
| Class 7 | Generative AI and LLM(2) | Understand the application of generative AI and large-scale language models. |
Out-of-Class Study Time (Preparation and Review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to course materials and so on.
Textbook(s)
N/A
Reference books, course materials, etc.
Handouts
Assessment criteria and methods
report
Related courses
- N/A
Prerequisites (i.e., required knowledge, skills, courses, etc.)
N/A
