Youngwook Kim

I am an Assistant Professor at School of Artificial Intelligence, College of Computer Science, Kookmin University.

I received my Ph.D degree from Department of Eletrical and Computer Engineering, Seoul National University, in 2024, under advisor Jungwoo Lee. Also, I received my bachelor's degree from Department of Civil and Environmental Engineering, Seoul National University, in 2018.

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AI VISION Lab (Applied & Intelligent VISION Lab) (https://aivision.kookmin.ac.kr/) 에서 함께 연구할 대학원생을 모집합니다. 관심있으신 분은 이메일로 문의 바랍니다.

I'm interested in computer vision, learning from noisy labels, multi-label learning, weakly supervised learning, and remote sensing.

We propose an automated curriculum learning solution for medical image registration that does not require expert knowledge or prior experience.

We introduce Dual Hierarchical Representation (DHR), which allows for faithful reconstructions under constrained computation.

We introduce generating instance-dependent multi-label noise into multi-label remote sensing image datasets which is more feasible and challenging noise scenario.

By investigating the difference in model explanation, we devise a simple but effective solution to compensate the damage by false negative labels.

By utilizing memorization effect, we can efficiently train multi-label classification model with small number of partially annotated labels.

The format of this website is borrowed from Jon Barron.