Abstract
The use of feedforward multilayer artificial neural network to detect European starling in vineyards is presented in this paper. In the first paragraphs, the idea of whole system is outlined. Then, the method of detection is described and demonstrated, the process of neural network design is illustrated and, in the end, the neural network is validated.
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References
Bisho J, McKay H, Parrot D, Allan J (2003) Review of international research literature regarding the effectiveness of auditory bird scaring techniques and potential alternatives. Central Science Laboratories
Potamitis I, Ntalampiras S, Jahn O, Riede K (2014) Automatic bird sound detection in long real-field recordings: applications and tools. Appl Acoust 80:1–9
Klein L, Mino R, Hovan M, Antonik P, Genello G (2004) Mmw radar for dedicated bird detection at airports and airfields. In: Radar conference, 2004. EURAD. First European, pp 157–160
Pornpanomchai C, Homnan M, Pramuksan N, Rakyindee W (2011) Smart scarecrow. In: 2011 Third international conference on measuring technology and mechatronics automation (ICMTMA), vol 3, pp 294–297
Viswanathan V, Makhoul J, Schwartz RM, Huggins A (1982) Variable frame rate transmission: a review of methodology and application to narrow-band lpc speech coding. IEEE Trans Commun 30(4):674–686
Sun R, Marye Y, Zhao HA (2013) Fft based automatic species identification improvement with 4-layer neural network. In: 2013 13th International symposium on communications and information technologies (ISCIT), pp 513–516
Gardner WR, Rao B (1995) Theoretical analysis of the high-rate vector quantization of lpc parameters. IEEE Trans Speech Audio Process 3(5):367–381
Rader C, Brenner N (1976) A new principle for fast fourier transformation. IEEE Trans Acoust Speech Signal Process 24(3):264–266
Markel J, Gray A (1976) Linear prediction of speech. Springer, Berlin
Hermansky H (1990) Perceptual linear predictive (plp) analysis for speech recognition. J Acoust Soc Am
Davis S, Mermelstein P (1980) Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Trans Acoust Speech Signal Process 28(4):357–366
McIlraith A, Card H (1995) Birdsong recognition with dsp and neural networks. In: WESCANEX 95: communications, power, and computing. Conference proceedings., IEEE. vol 2, pp 409–414 vol 2
Haykin S (1999) Neural networks: a comprehensive foundation. Prentice Hall (1999) ISBN: 0132733501
Nguyen H, Prasad N, Walker C (2003) A first course in fuzzy and neural control. Chapman and Hall/CRC. ISBN: 1584882441
Hagan M, Menhaj M (1994) Training feedforward networks with the marquardt algorithm. IEEE Trans Neural Networks 5(6):989–993
Kiktova E, Lojka M, Pleva M, Juhar J, Cizmar A (2013) Comparison of different feature types for acoustic event detection system. In: Dziech A, Czyżewski A (eds) MCSS 2013, vol 368., CCISSpringer, Heidelberg, pp 288–297
Kiktova-Vozarikova E, Juhar J, Cizmar A (2003) Feature selection for acoustic events detection. Multimedia Tools Appl 1–21
Acknowledgments
The work has been supported by the funds of the IGA, University of Pardubice, Czech Republic, project number SGSFEI2015006. This support is very gratefully acknowledged. In addition, this article was published within the sustainability of the project “Support of short term attachments and skilful activities for innovation of tertiary education at the Jan Perner Transport Faculty and Faculty of Electrical Engineering and Informatics, University of Pardubice, registration no. CZ.1.07/2.4.00/17.0107”.
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Dolezel, P., Mariska, M. (2015). Neural Networks and Linear Predictive Coding Coefficients Used for European Starling Detection in Vineyards. In: Herrero, Á., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds) 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 368. Springer, Cham. https://doi.org/10.1007/978-3-319-19719-7_8
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DOI: https://doi.org/10.1007/978-3-319-19719-7_8
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