Hyovin Kwak

Deep Learning Intern at Pro2Future GmbH
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Contact Information
us****@****om
(386) 825-5501
Location
Dortmund, North Rhine-Westphalia, Germany, DE
Languages
  • English (iBT Score: 103/120) Professional working proficiency
  • Deutsch (telc Deutsch C1 Hochschule, bestanden, Gesamtpunkte: 170/214) Professional working proficiency
  • 한국어 Native or bilingual proficiency

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Experience

    • Austria
    • Research
    • 1 - 100 Employee
    • Deep Learning Intern
      • Oct 2021 - Present

      -Implementation of edge/corner points detection and open curve proposal of PIE-NET(Wang et al.,2020) based on PointNet++-Setting up a deep learning pipeline based on detection and proposals to extract tunnel profile data e.g. orthogonal cross sections, center axis points approximation(+curve fitting) based on tunnel point cloud data-Processing the ABC Dataset(Koch et al., 2019) to validate the pipeline-Preparation for regular meetings with project partners-(next) Implementation of curve decompositions and research publications

    • Austria
    • Research
    • 1 - 100 Employee
    • Deep Learning Intern
      • Jan 2021 - Mar 2021

      -Setting up pipelines to train/evaluate object detection models in the framework of Tensorflow2 Object Detection API and Detectron2 to detect objects in tunnel images -Setting up pipelines to train/evaluate object detection models in the framework of Tensorflow2 Object Detection API and Detectron2 to detect objects in tunnel images

    • Germany
    • Higher Education
    • 700 & Above Employee
    • Studentische Hilfskraft, Lehrstuhl12, Fakultät Informatik
      • Jun 2019 - Oct 2020

      - Building a prototype based on Python from what's once already implmented in C++ so that users can compare several face recognition algorithms (e.g. Eigenfaces, Fisherface, LBP faces) and detect faces real time-Implementation of VGG16 face recognition demo-Implementation of FASTER R-CNN face detection and recognition demo in framework of PyTorch-Minor UI developments(PySide2, PyQt) - Building a prototype based on Python from what's once already implmented in C++ so that users can compare several face recognition algorithms (e.g. Eigenfaces, Fisherface, LBP faces) and detect faces real time-Implementation of VGG16 face recognition demo-Implementation of FASTER R-CNN face detection and recognition demo in framework of PyTorch-Minor UI developments(PySide2, PyQt)

    • Broadcast Media Production and Distribution
    • 1 - 100 Employee
    • Broadcast Producer
      • Jul 2012 - Feb 2014

      -Military obligation, KATUSA(Korean Augmentation to the US Army) Sergeant -Military obligation, KATUSA(Korean Augmentation to the US Army) Sergeant

Education

  • Technische Universität Dortmund
    Master of Science - MS, Datenwissenschaft (Data Science)
    2018 -
  • Konkuk University
    Bachelor of Arts - BA, Applied Statistics
    2011 - 2017

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