Infrared Target Detection using Shallow CNNs

Uzun E., Aksoy T., Akagunduz E.

28th Signal Processing and Communications Applications Conference (SIU), ELECTR NETWORK, 5 - 07 Ekim 2020 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu49456.2020.9302501
  • Basıldığı Ülke: ELECTR NETWORK
  • Anahtar Kelimeler: infrared target detection, shallow networks, two step learning
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

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.