Infrared Target Detection using Shallow CNNs

Date

2020-01-01

Author

Uzun, Engin
Aksoy, Tolga
Akagündüz, Erdem

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Convolutional Neural Networks can solve the target detection problem satisfactorily. However, the proposed solutions generally require deep networks and hence, are inefficient when it comes to utilising them on performance-limited systems. In this paper, we study the infrared target detection problem using a shallow network solution, accordingly its implementation on a performance limited system. Using a dataset comprising real and simulated infrared scenes; it is observed that, when trained with the correct training strategy, shallow networks can provide satisfactory performance, even with scale-invariance capability.

URI

https://hdl.handle.net/11511/93988

DOI

https://doi.org/10.1109/siu49456.2020.9302501

Conference Name

28th Signal Processing and Communications Applications Conference (SIU)

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

E. Uzun, T. Aksoy, and E. Akagündüz, “Infrared Target Detection using Shallow CNNs,” presented at the 28th Signal Processing and Communications Applications Conference (SIU), ELECTR NETWORK, 2020, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/93988.