Fürkan Elibol

Linkedin: https://www.linkedin.com/in/felibol/
Github: https://github.com/felibol

Objective

As a well-qualified and experienced software developer, I am seeking a position in the field of computer vision and/or image processing.

Education

PhD in Computer Science - Christian-Albrecht University of Kiel, Kiel (2019 – Not completed. Quit in 2020)
PhD Thesis: Finding Correspondences Between Underwater Images Despites Moving Lights and Water Effects

  • Used Technologies: C/C++, Python, OpenCV
  • Publications: “Deep sea robotic imaging simulator”, International Conference on Pattern Recognition (ICPR), 2021

PhD in Electronics Engineering - Özyeğin University, Istanbul (2012 – Not completed. Quit in 2016)
PhD Thesis: Fusing Inertial Sensor Data in Extended Kalman Filter for 3D Camera Pose Tracking

  • Used Technologies: C/C++, OpenCV, Matlab, ROS

MSc. in Electronics and Communication Engineering - Istanbul Technical University, Istanbul (2009 – 2012)
MSc Thesis: Wavelet Transform-Based Image Resolution Enhancement of Electromagnetic Information Leakage Images

  • Used Technologies: C, Matlab, LabWindows/CVI, National Instruments PXI based RF Hardware
  • Publications: “Realistic eavesdropping attacks on computer displays with low-cost and mobile receiver system”, Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European

BSc. in Electrical and Electronics Engineering - Ege University, Izmir (2003 – 2008)
BSc Thesis: Classification of Alertness by Human EEG

  • Used Technologies: Matlab, C
  • Publications: “Investigation of New Statistical Features for BCI based Sleep Stages Recognition through EEG Bio-signals”, Springer - Lecture Notes in Bioinformatics

Experience

Senior Computer Vision Engineer - Bepro Europe GmbH, 20457 Hamburg, GERMANY (08.2020 – present)

  • Algorithms developed for multi-camera geometric calibration
  • Multiple camera synced RTSP stream receiver implemented based on Live555 library
  • Performance enhancements for computer vision pipelines on Nvidia Jetson platforms
  • Sports field segmentation with U-Net
  • Sports field marking detection using two conditional GANs
  • Used Technologies: Python, C++, OpenCV, Pytorch, Git, Jira, Nvidia Jetson

Senior Computer Vision Researcher - GEOMAR Helmholtz Center for Ocean Research, 24148 Kiel, GERMANY (08.2019 – 08.2020)

  • Algorithm development for mapping and 3D structure creation of deep sea floor from images taken with AUV (Autonomous Underwater Vehicle)
  • Used Technologies: C++, OpenCV, Python

Senior Software Developer - Haivision Network Video GmbH, 24768 Rendsburg, GERMANY (07.2016 – 08.2019)

  • Intel Media SDK based encoder, decoder and video processing pipelines have been implemented.
  • CEA-608 Closed Caption decoder has been implemented.
  • SMPTE ST2022-

Skills

  • Proficient in C/C++, Python, OpenCV, Matlab, ROS, Git, Jira, Pytorch, LabWindows/CVI, National Instruments PXI, and Ettus Research USRP SDR devices.
  • Experienced in developing computer vision, image processing, and machine learning algorithms and applications such as people/vehicle tracking, video stabilization, mosaicing, georeferencing of orthophotos, simultaneous localization and mapping (SLAM), deep sea robotic imaging simulator, multi-camera geometric calibration, and sports field segmentation.
  • Familiar with embedded Linux (Angstrom) and NVIDIA Jetson platforms.
  • Strong background in electromagnetic information security (TEMPEST) applications and software-defined radio (SDR) based radio frequency (RF) applications.
  • Excellent communication and problem-solving skills.

References

Available upon request.