Acknowledgement
이 논문은 2024학년도 제주대학교 교원성과지원사업에 의하여 연구되었음.
References
- H. J. Lee, I. S. Seo, and K. S. Bae, "Separation of passive sonar target signals using frequency domain independent component analysis" (in Korean), J. Acoust. Soc. Kr. 35, 110-117 (2016).
- R. J. Urick, Principles of Underwater Sound (McGraw-Hill, New York, 1993), pp. 302-310.
- J. K. Ahn, H. D. Cho, D. Shin, T. Kwon, and G. T. Kim, "LOFAR/DEMON grams compression method for passive sonar" (in Korean), J. Acoust. Soc. Kr. 39, 28-46 (2020).
- S. E. Lee, S. B. Hwang, and D. Y. Noh, "A study on the algorithm for underwater target automatic classification using the passive sonar" (in Korean), J. KIMS Technol. 3, 76-84 (2000).
- H. S. Kim, "Intelligent feature extraction and scoring algorithm for classification of passive sonar target" (in Korean), J. Korean Inst. Intell. Syst. 19, 629-634 (2009).
- J. d. C. V. Fernandes, N. N. de Moura Junior, and J.M. de Seixas, "Deep learning models for passive sonar signal classification of military data," Remote Sens. 14, article no. 2648 (2022).
- C. Satheesh, S. Kamel, A. Mujeeb, and M. H. Supriya, "Passive sonar target classification using deep generative β-VAE," IEEE Signal Process Lett, 28, 808-812 (2021).
- V. S. Doan, T. Huynh-The, and D. S. Kim, "Underwater acoustic target classification based on dense convolutional neural network," IEEE Geosci. Remote Sens. Lett. 19, 1-5 (2022).
- S. Kim, S. K. Jung, D. Kang, M. Kim, and S. Chon, "Application of the artificial intelligence for automatic detection of shipping noise in shallow-water" (in Korean). J. Acoust. Soc. Kr. 39, 279-285 (2020).
- K. B. Lee, G. H. Ko, and C. H. Lee, "Passive sonar signal classification using attention based gated recurrent unit" (in Korean). J. Acoust. Soc. Kr. 42, 345-356 (2023).
- S. Kamal, C. S. Chandran, and M. H. Supriya, "Passive sonar automated target classifier for shallow waters using end-to-end learnable deep convolutional LSTMs," Eng. Sci. Technol. an Int. J. 24, 860-871 (2021).
- F. Liu, T. Shen, Z. Luo, D. Zhao, and S. Guo, "Underwater target recognition using convolutional recurrent neural networks with 3-D Mel-spectrogram and data augmentation," Appl. Acoust. 178, article no. 107989 (2021).
- P. H. C. Avelar, A. R. Tavaras, T. L. T. da Silveira, C. R. Jung, and L. C. Lamb, "Superpixel image classification with graph attention networks," Proc. 33rd SIBGRAPI, 203-209 (2020).
- P. Sellars, A. I. Aviles-Rivero, and C. B. Schonlieb, "Superpixel contracted graph-based learning for hyperspectral image classification," IEEE Trans Geosci Remote. 58, 4180-4193 (2020).
- C. Aironi, S. Cornell, E. Principi, and S. Squartini, "Graph-based representation of audio signals for sound event classification," Proc. 29th EUSIPCO, 566-570 (2021).
- Y. C. Jung, B. U. Kim, S. K. An, W. J. Seong, and K. H. Lee, "An algorithm for submarine passive sonar simulator" (in Korean), J. Acoust. Soc. Kr. 32, 472-483 (2013).
- M. Deaett, "Signature modeling for acoustic trainer synthesis," IEEE J. Ocean. Eng. 12, 143-147 (1987).
- S. H. Kang, "A study on the Lloyd's mirror effect on the underwater radiated noise for the underwater vehicle" (in Korean), J. Acoust. Soc. Kr. 40, 314-319 (2021).
- L. E. Kinsler, A. R. Frey, A. B. Coppens, and J. V. Sanders, Fundamentals of Acoustics (John Wiley & Sons, New Jersey, 1999), pp. 446-448.
- M. Zhang, Z. Cui, M. Neumann, and Y. Chen, "An end-to-end deep learning architecture for graph classification," Proc. 32nd AAAI. Conf. Artificial Int. 4438- 4445 (2018).
- T. N. Kipf and M. Welling, "Semi-supervised classification with graph convolutional networks," arXiv preprint, (2016).
- N. Shervashidze, P. Schweitzer, E. J. Van Leeuwen, K. Mehlhorn, and K. M. Borgwardt, "Weisfeiler-lehman graph kernels," J. Mach. Learn. Res. 12, 2539-2561 (2011).
- Z. Ying, J. You, C. Morris, X. Ren, W. Hamilton, and J. Leskovec, "Hierarchical graph representation learning with differentiable pooling," 32nd Adv. Neural Inf. Process. Syst. 1-11 (2018).
- D. S. Domingues, S. T. Guizarro, A. C. Lopez, and A. P. Gimenez, "ShipsEar: An underwater vessel noise database," Appl. Acoust. 113, 64-69 (2016).