A dataset of infrared images for deep learning based drone detection
Publication date
2024-03-21
Document type
Konferenzbeitrag
Organisational unit
Allgemeine Nachrichtentechnik
Conference
17th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2023) ; Bangkok, Thailand ; November 8–10, 2023
Publisher
IEEE
Book title
2023 17th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
Part of the university bibliography
✅
Language
English
Abstract
Recently, drone detection has become a topic of interest due to the widespread usage of drones in various applications, particularly for recreational purposes. Such detection tasks are usually performed by deep learning models which require different kinds of image datasets to be trained on. Hence, a dataset of infrared images for drone detection is introduced in this paper. In order to generate the dataset, videos of drones are captured initially with multiple cameras at two different locations. The video frames are then extracted and the drones are annotated with the help of an annotation tool and an automated script. A comprehensive analysis of the dataset is provided and multiple configurations of a selection of CNN models are trained on a fraction of the dataset. The trained models are employed on the test dataset and their performance is evaluated.
Version
Published version
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Metadata only access