Johan Hjorth, Doctoral student

Johan Hjorth received a Master of Science in Dependable Systems from Mälardalen University in 2020. Thesis title: "Towards Reliable Computer Vision in Aviation: An Evaluation of Sensor Fusion and Quality Assessment."
As of 2020, Johan Hjorth is enrolled as a PhD student at Mälardalen University.

My research focus is on mitigation techniques in safety-critical embedded systems using deep neural networks. The work includes both symmetric and systematic faults which can lead to system failures.

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Latest publications:

A novel method for detecting UAVs using parallel neural networks with re-inference (Sep 2022)
Hubert Stepien , Martin Bilger , Håkan Forsberg, Billy Lindgren , Johan Hjorth
33rd Congress of the International Council of the Aeronautical Sciences (ICAS 2022)

Challenges in Using Neural Networks in Safety-Critical Applications (Oct 2020)
Håkan Forsberg, Johan Hjorth, Masoud Daneshtalab, Joakim Lindén, Torbjörn Månefjord
The 39th Digital Avionics Systems Conference (DASC'2020)