Giseong Hwang is an undergraduate student in Internet of Things at Soonchunhyang University and an Undergraduate Intern at IMSI Research Lab. His research focuses on AI for gastrointestinal endoscopy, including segmentation and classification from clinical images and videos.
He is particularly interested in self-supervised and weakly supervised learning for settings where dense medical annotations are difficult to obtain. With strong practical experience in video preprocessing, temporal sampling, and frame-level analysis, he develops reliable pipelines for endoscopic video understanding and CNN-based medical imaging experiments.
As a contributor to the BDOT collaboration, he supports SSDenoDet research on self-supervised cross-domain feature denoising for SAR target detection. His contributions include running and analyzing CNN baselines and controlled experiments that help evaluate model behavior across sensing domains.
Research Interests
- Gastrointestinal Endoscopy AI
- Medical Image Segmentation & Classification
- Video Understanding
- Self-Supervised Learning
- Weakly Supervised Learning
- CNN Experimentation
Education
- B.S. studies in Internet of Things
Soonchunhyang University
Research Activities
- Endoscopy segmentation and classification
- BDOT / SSDenoDet collaboration
Selected Research Contribution
- SSDenoDet: Self-Supervised Cross-Domain Feature Denoising for SAR Target Detection — contributed CNN experiments and comparative analysis within the BDOT team.
Recent Publications
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