I am a researcher in the field of machine learning with a focus on computer vision. My research interests include the foundations of algorithms and their real-world applications through machine learning and statistical pattern analysis.
I have a background in architectural engineering, having graduated from Pusan National University (PNU) and obtaining my MS in civil and environmental engineering from the Korea Advanced Institute of Science and Technology (KAIST). My master's thesis involved the use of computer vision and image processing techniques for defect detection. Since then, I have been deeply engaged in the field of artificial intelligence, constantly expanding my knowledge through work experience.
My professional experience began at Cafe24 Corp, where I developed computer vision-based web service solutions for the e-commerce market, such as image inpainting, interactive segmentation, dominant color analysis, and landmark detection. After then, I worked on vessel detection project for autonomous navigation system at Avikus.
Now, I am working on deep learning modeling and optimization for Neural Processing Unit(NPU) at SAPEON Korea Inc.
Date | Task Type | Research Title |
---|---|---|
Jun.2021~Mar.2023 | Object Detection | Development of vision based marine intelligent navigation assistant system |
Nov.2020~May.2021 | Landmark Detection | Fashion product size-charting automation based on landmark detection |
Jun.2020~Dec.2020 | Color Quantization | Dominant color extractor using K-means clustering |
Nov.2019~Aug.2020 | Object Segmentation | Super-detail model object segmentation |
Apr.2019~Dev.2019 | Image Generation | Real-time object removal and background restoration |
Feb.2017~Aug.2018 | Image Classification | Development of micro-crack detection system in Flexible OLED using laser thermography |
Aug.2016~Feb.2017 | Image Processing | Large-scale infrastructure monitoring and management using unmanned inspection units |
Jul.2016~Jun.2017 | Outlier Detection | Development of automated non-destructive inspection system for damage detection in triplex adhesive layers |