Seoul, South Korea
1) 연구/기술 분야 - Computer Vision / Machine Learning / Computer Security / Medical Imaging 2) 딥러닝 연구 분야 - AutoML, Self-Supervised Learning, 3D deep learning, HPE(Human Pose Estimation) - Classification : EfficientNet-V1, EfficientNet-V2, BiT(Big Transfer) - Detection : YoloV4, YoloV5 - Segmentation : DeepLabV3, M-RCNN - DL model Conversion and Compiler : LibTorch, TorchScript, ONNX, OpenVINO, TensorRT, TIS, TVM 3) S/W V&V 4) 사업기회 - 생산 품질검사를 위한 2D/3D 머신비전, 공장자동화를 위한 로봇비전, 공장시설의 상태기반 유지보수에 컴퓨터비전 적용 - 스마트시티의 video surveillance, 지능형 CCTV 개발 및 적용(엣지 컴퓨팅) - 3D 딥러닝을 기술을 자율 주행 영역에 적용
o Instructor in Deep Learning Course (Textbook "Deep Learning with Python" by Francois Chollet) o Training Program (in house teaching program for CV, ML, DL, CS) o Computer Vision o Machine Learning (3D Deep Learning, HPE) - Deep Learning for 3D Data (RGBD, Point Cloud) - Human Pose Estimation(Top-Down, Bottom-Up) - Classification : EfficientNet-V1, EfficientNet-V2, BiT(Big Transfer) - Detection : YoloV4, YoloV5 - Segmentation : DeepLabV3, M-RCNN - DL Model Conversion & Compiler : LibTorch, TorchScript, ONNX, OpenVINO, TensorRT, TIS, TVM o Machine Vision - Defect Classification in Manufacturing Line(Beer Company) - Detect poor welding condition in Hair-pin Motor Production Line o Energy Saving Solution - Develop AI solutions using FEMS data - Classical ML or Deep Learning
Computer Vision Machine Learning(Deep) Information Security
I&C Design for NPP
I&C Design for NPP