This course is specifically designed for high schools students with an interest in AI and its applications.
This course includes:
- 5 full-day lectures and laboratory, from 9:30am-4:30pm.
- One-day visit to Prof. Xiang’s Laboratory at the University of Michigan, Dearborn Campus.
- Guidance from College teaching assistants.
- Lesson on leading AI topics: objective detections, facial, and character recognitions based on openCV and convolution neural network.
- Content focusing on Raspberry Pi programming and AI applications
In this course, you will gain:
- A solid foundation in both AI as well as the latest technologies in image processing and deep neural networks.
- Advanced Python programming skills.
- Hardware and real-world experience.
- Exposure to the world of AI and the opportunity to explore your interest in this promising but intensive field.
Course Syllabus The syllabus for the 5-day course is detailed below:
- Day 1: Advanced Python programming (morning). Raspberry Pi and Lab visit (Afternoon)
- Day 2: Image processing (morning) and license plate recognition (afternoon)
- Day 3: Neural network basics (morning) and character recognition based on convolution neural network (afternoon).
- Day 4: Leading deep neural network (morning) and objective detections (afternoon).
- Day 5: Creating and training your own neural network (morning) and project demonstration (afternoon).
This course requires students to have a strong interest in AI and its applications, in addition to proficient Python programming skills.
- 1. A Computer
- 2. A Raspberry Pi and Pi camera (optional)
Prof. XiangDr. Weidong Xiang is a full professor in the Department of Electrical and Computer Engineering at the University of Michigan Dearborn. His research focuses on vehicular communications and networks, 5G, autonomous driving, Internet of things, and wireless control systems.
He established and leads the Center for Vehicular Communications and Network Laboratory at UMD which focuses on vehicular communications and network, autonomous driving, IoT, and machine learning in wireless communications. He has published 100+ technical papers in relevant international journals and conferences. As the principal investigator, Dr. Xiang has accomplished more than 20+ grants with a total amount more than $2,000,000 in the past decades, including sponsors such as NSF (4), DoE (1), Ford (2), GM (1), LGE(1), CISCO(1), Mcity(1) and the University of Michigan (6).
Over the years, he has supervised more than 50 doctoral students, master students, visiting scholars. Many of these students now work at the research center of top companies including: Apple, Intel, Qualcomm, Ford and GM Car companies, etc. Currently, Dr. Xiang is guiding three Ph.D. students, all studying machine learning in wireless communications and network through funded projects and experimental data. He received Faculty Excellent Research Award, 2019 from the College of Engineering and Computer Science at the University of Michigan-Dearborn.
In 2020, Dr. Xiang has already filed an invention disclosure for xBOT.