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Keynote Speakers MAPR 2022 - Professor Kanghyun Jo (School of Engineering University of Ulsan Korea)

October 13, 2022 at 1:30 - 2:15 PM

Kanghyun Jo, Professor and Faculty Dean, School of Electrical Engineering,University of Ulsan, Korea.

Kang-Hyun Jo (Senior Member, IEEE) received the Ph.D. degree in computer controlled machinery from Osaka University, Osaka, Japan, in 1997. He joined the School of Electrical Engineering, University of Ulsan, Ulsan, South Korea where currently serving as the Faculty Dean.

His research interests include computer vision, robotics, autonomous vehicle, and ambient intelligence. He has served as the Director or an AdCom Member for the Institute of Control, Robotics and Systems(currently Vice-President, Fellow member), The Society of Instrument and Control Engineers, and the IEEE IES Technical Committee on Human Factors Chair, an AdCom Member, and the Secretary until

2019.

He has also been involved in organizing many international conferences, such as the International Workshop on Frontiers of Computer Vision, the International Conference on Intelligent Computation, the International Conference on Industrial Technology, the International Conference on Human System Interactions, and the Annual Conference of the IEEE Industrial Electronics Society. He is also an Editorial Board Member for international journals, such as the International Journal of Control, Automation, and Systems. He has published more than 200 technical papers with the peer-reviews. It’s worth reading his latest works in top-tier journals like IEEE Trans. Industrial Informatics(TII, IF: 11.648) and Trans. Industrial Electronics(TIE, IF: 8.236).

Talk: Drone Imagery for Artificial Intelligence Service 

In the talks, I will deliver how the drone images are worth for AI services. As an example, in Korean National Grants how the drone images were established for AI services. As the PM of the drone image in year 2020, I exchange the program outline and the scope of the images from the autonomous drone’s viewpoint. General approaches with deep learning models render the bounding boxes of the objects in the classification tasks and the model works. Data processing for the AI data for the researchers is also interesting issue so that the examples of approaches and processing tools will be delivered. Finally, I will explain the AI data archives including drone images in AIHub(aihub.or.kr currently in Korean) and other valuable data which will be released continuously. Some AI service examples are also explored and demonstrated in the talks.

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