오효근

산업 분야: B2B, SaaS, AI

스킬: python, 머신 러닝, PyTorch, Docker, Linux, git, Kubernetes

AI-based OCR Solution, TwinReader (2023. 02 ~ 2024. 09) - Developed a Kubernetes-based Triton Inference Server for model deployment. - Resolved source and version control challenges during Triton Inference Server deployment by improving the architecture using GitLab CI and Kubernetes. - Fixed critical flaws in the Triton Inference Server. (GPU Memory reduced by 47.9%) - Enhanced inference time of the text detection model using TensorRT. (inference time decrease by 87.31%) Python Library for Pre/Post-Processing, Visualization, and Model Backend (2023. 10 ~ 2024. 09) - Maintained the integrity of the library through type hints and PyTest. - Standardized the preprocessing of various document images and visualization of model inference results. - Improved the post-processing speed of the text detection model through algorithm enhancements using Cython. (inference time decreased by 74.12%)

Hyogeun Oh, et al. Classification and Redundancy Quantitative Evaluation Algorithm for Highly Efficient Fault Diagnosis of Rotary Machines in Roll-to-Roll systems, Measurement (JCR 17.19%), 2023 Hyogeun Oh, et al. Feature Selection Algorithm Based on Density and Distance for Fault Diagnosis Applied to a Roll-to-Roll Manufacturing System, Journal of Computational Design and Engineering (JCR 10.87%), 2022