A novel method for detecting uavs using parallelneural networks with re-inferenceShow others and affiliations
2022 (English)Conference paper, Published paper (Refereed)
Abstract [en]
In this paper, we present a novel method for detecting UAVs using diverse parallel neural networks with re-inference. The parallel networks are of type Convolutional Neural Networks (CNNs). We first set up a lowthreshold (2 respectively 20%) for each of the individual networks to detect a flying object. If all networks detecta flying object in the same area of a video frame with some overlap, we zoom into that area and redo the objectdetection and classification (re-inference step). To ensure correctness and reliability of the results from severalparallel CNNs, we introduce total confidence Tc as a measurement. We also introduce the intersection overunion for multiple parallel networks, IoUAll , and use that as threshold for calculating a reliable Tc . The resultsshow great improvements regarding accurate detection of flying drones, reduced mispredictions of otherobjects as drones, and fast response time when drones disappear from the scene.
Place, publisher, year, edition, pages
2022. Vol. 9, p. 6756-6769
Series
ICAS Proceedings, ISSN 2958-4647
Keywords [en]
drones, detection, neural networks, re-inference, redundancy
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-61285ISBN: 9781713871163 (print)OAI: oai:DiVA.org:mdh-61285DiVA, id: diva2:1719447
Conference
33rd Congress of the International Council of the Aeronautical Sciences, Stockholm, Sweden, 4-9 September, 2022
2022-12-152022-12-152023-05-31Bibliographically approved