Với mục tiêu mang đến cho các sinh viên chương trình đào tạo tiên tiến những bài giảng đến từ các giáo sư uy tín trên thế giới, trong khuôn khổ hợp tác với trường Đại học Deakin (Úc), Trường Công nghệ Thông tin và Truyền thông tổ chức buổi workshop với chủ đề “How Does AI See? From Pixels to Intelligent Machines” bởi GS. Duc Thanh Nguyen
Workshop được tổ chức lúc 14:00 ngày 16/10/2026 tại C7-223, Đại học Bách khoa Hà Nội
Thông tin bài trình bày
How Does AI See? From Pixels to Intelligent Machines
Abstract
This demo class introduces students to the fascinating world of Artificial Intelligence and Computer Vision. Starting from the simple question “How does a computer see?”, students will discover how digital images are represented and how neural networks learn to recognize objects. Students will experiment with image classification and object detection, allowing them to see an AI system identify and locate objects in real-world images. The class will also explore an important question: “Can we fool AI?” By answering this question, students will see how AI predictions can change and why AI systems can make mistakes.
Duc Thanh Nguyen
Senior Lecturer, Faculty of Science Engineering and Built Environment, School of Information Technology
Deakin University (Australia)
Bio
Thanh Nguyen (aka Duc Thanh Nguyen) received his Ph.D. degree in Computer
Science from the University of Wollongong (UOW), Australia, in 2012. From 2013
to 2016, he had held various research positions including research associate,
postdoctoral research fellow at UOW, Singapore University of Technology and
Design, and Deakin University. Currently, he is a Senior Lecturer of Computer
Science in the School of Information Technology, Deakin University.
Dr Nguyen’s research interests include Computer Vision and Pattern
Recognition. He has published his work in highly ranked publication venues in
Computer Vision and Pattern Recognition such as Pattern Recognition journal,
CVPR, ICCV, ECCV, AAAI.
Dr Nguyen has attracted and managed competitive national/international
research funding with a total income over $2.5 mil AUD.
