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Drones in Security and Surveillance – Anomaly Detection for Aerial Surveillance

PhD defence, Friday, 03 December 2021. Ilker Bozcan

2021.12.03 | Mette Nielsen

Ilker Bozcan

During his Ph.D. studies, Ilker Bozcan researched the detection of abnormal observations in aerial images captured by drones. In particular, Ilker Bozcan focused on developing artificial intelligence-based methods that can learn patterns in an environment without human supervision. The proposed methods are utilized for aerial surveillance scenarios, in which a drone mounted with a camera is deployed for monitoring outdoor or indoor environments.

The new research findings contribute to the understanding of how to design the anomaly detection framework that is suitable for surveillance applications and potentially provides technologies to increase safety in society.


The PhD study was completed at Department of Electrical and Computer Engineering, Faculty of Technical Sciences, Aarhus University.

This summary was prepared by the PhD student.

Time: Friday, 03 December 2021 at 14:00
Place: Building 5125 Edison Building, room 417, Department of Electrical and Computer Engineering, Aarhus University, Skejby Nordlandsvej 301, 8200 Aarhus N.

Title of PhD thesis: Learning-based Anomaly Detection for Aerial Surveillance

Contact information: Ilker Bozcan, e-mail: ilker@ece.au.dk and bozcanilker@gmail.com, tel.: +45 50358672

Members of the assessment committee:
Professor Marco Hutter, Department of Mechanical and Process Engineering, ETH Zurich, Switzerland
Associate Professor  Lazaros Nalpantidis, Department of Electrical Engineering, Technical University of Denmark (DTU), Denmark
Professor Preben Kidmose (chairman), Department of Electrical and Computer Engineering, Aarhus University, Denmark

Main supervisor:
Associate Professor Erdal Kayacan, Department of Electrical and Computer Engineering, Aarhus University, Denmark

Language: The PhD dissertation will be defended in English

The defence is public.
The PhD thesis is available for reading at the Graduate School of Technical Sciences/GSTS, Katrinebjergvej 89F, building 5132, 8200 Aarhus N.

PhD defence
17427 / i43