Emre Gülsoylu

Research Associate at
Computer Vision Research Group,
Department of Informatics,
University of Hamburg

Experience

University of Hamburg
11.2023 - Present
uni-hamburg.de

Research Associate at Computer Vision Research Group

Working in InteGreatDrones project.

Fraunhofer CML
05.2022 - 10.2023
cml.fraunhofer.de

Student Research Assistant

Assisted the Maritime Informatics Team in their research projects while working on my master's thesis.

  • Conducted a study on vessel detection and georeferencing by AIS-Image fusion.
  • Worked on distance prediction for an Unmanned Surface Vehicle.
  • Wrote a master thesis on vessel hull segmentation and course over ground prediction.
University of Hamburg
10.2021 - 03.2022
uni-hamburg.de

Student Tutor

Assisted the lecturers in conducting exercise classes for the Computer Vision I Course.

  • Created new assignments, and provided feedback on existing assignments/quizzes.
  • Answered assignment or quiz related questions of students.
Delphi Technologies
Izmir, Turkey
09.2018 - 07.2019
delphi.com

Systems Student Engineer

Developed and updated system models in Matlab/Simulink, and conducted functional tests for Selective Catalytic Reduction or Engine Safety Monitoring systems.

Delphi Technologies
Izmir, Turkey
08.2017 - 09.2017
delphi.com

Intern

Developed an application that automates the execution of basic functional integration tests and generates the test results in the form of an Excel document.

Education

University of Hamburg
2020 - 2023
uni-hamburg.de
Intelligent Adaptive Systems (M. Sc.)
  • Master's Thesis: Predicting the Course Over Ground of Ships by Segmenting Hull Sections from an Image Using Deep Learning
  • Project: Active Visual Object Search in Household Environments
  • Independent Study: Image and IAS Data Fusion for Vessel Identification
  • Independent Study: Journal Recommendation System for Scientific Papers Targeted to the TRIndex
Manisa Celal Bayar University
2015 - 2019
mcbu.edu.tr
Computer Engineering (B. Sc.)
  • Bachelor Thesis: A Machine Vision System for Raisin Quality Grading
  • Design Project: A Machine Vision System for Pest Recognition on Grapvine Pheremon Traps
  • Made a series of presentations regarding the research project competitions and fellowship programmes for undergraduate students.
Technische Hochschule Ingolstadt
2017 - 2018
thi.de
Erasmus+ Exchange Student
Attended courses such as Artificial Intelligence and Machine Learning, Automation Technologies within Erasmus+ Programme.

Publications

  • Gülsoylu, E., Koch, P., Yildiz, M., Constapel, M., & Kelm, A. P. (2024). Image and AIS Data Fusion Technique for Maritime Computer Vision Applications. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 859-868). [Paper] [CVF] [arXiv] As part of 2nd Workshop on Maritime Computer Vision (MaCVi).
  • Gülsoylu, E., Çipiloğlu Yıldız, Z. (2023). e-ksper: A Convolutional Neural Network Based System for Seedless Raisin Quality Grading. Gazi Journal of Engineering Sciences, vol. 9, no. 3, pp. 453-466. doi: 10.30855/gmbd.0705079 [Paper] [DergiPark]
  • Gulsoylu, E., Cipiloglu Yildiz, Z. (2020) Recognition of European Grapevine Moths on Pheromone Traps by Convolutional Neural Networks. International Conference on Advanced Technologies, Computer Engineering and Science (pp. 3). [Abstract]

Awards and Grants

  • Received a grant from The Scientific and Technological Research Council of Turkey (TÜBİTAK) Research Projects Fellowship Programme for Undergraduate Students (2209-A) in 2019.
  • Achieved 1st place at the "Research Projects Competition for Undergraduate Students (2242)" conducted by TÜBİTAK and "Young Brains, New Ideas" competition conducted by Information Technologies Foundation of Turkey, in recognition of the development of a machine vision system for raisin quality grading in 2019.

Design Registrations

  • Design Registration: Raisin Quality Grading Device (2019/06795)

Languages

    Languages: English (Fluent), German (A2.1), Turkish (Native)
    IELTS Academic overall score: 7.5 (L:7.5, R:8.5, W:6.5, S:6.5)