Time-delay recurrent neural network for exo-atmospheric infrared target recognition

Tao Liu; Jiang-bei Lv; Shu-hong Wong; Xiang Li

doi:10.1117/12.834570

5 August 2009 Time-delay recurrent neural network for exo-atmospheric infrared target recognition

Tao Liu, Jiang-bei Lv, Shu-hong Wong, Xiang Li

Proceedings Volume 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications; 738346 (2009) https://doi.org/10.1117/12.834570
Event: International Symposium on Photoelectronic Detection and Imaging 2009, 2009, Beijing, China

Abstract

A time-delay recurrent neural network (TDRNN) is proposed for exo-atmospheric infrared target recognition. The TDRNN employs adaptive time delays and recurrences where the adaptive time delays make the network choose the optimal values of time delays for the temporal location of important information in the input sequence and the recurrences enable the network to have dynamic recognition function. A TDRNN is trained and tested using simulated data. The target recognition experiment suggests that TDRNN have a better recognition ability.

Citation Download Citation

Tao Liu, Jiang-bei Lv, Shu-hong Wong, and Xiang Li "Time-delay recurrent neural network for exo-atmospheric infrared target recognition", Proc. SPIE 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, 738346 (5 August 2009); https://doi.org/10.1117/12.834570

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