Adavanne, S., Drossos, K., Çakir, E., Virtanen, T., Stacked convolutional and recurrent neural networks for bird audio detection. Signal Processing Conference (EUSIPCO), 2017 25th European, 2017, IEEE, 1729–1733.
Blume, D., Schwarzspecht, Grünspecht, Grauspecht: Dryocopus martius, Picus viridis, Picus canus. 5th ed., 1996, Die Neuhe Brehme-Bücherei. Westarp Wissenschaften, Magdeburg.
Blume, D., Tiefenbach, J., Die Buntspechte (Gattung picoides). 1997, Die Neuhe Brehme-Bücherei. Westarp Wissenschaften, Magdeburg.
Blumstein, D.T., Mennill, D.J., Clemins, P., Girod, L., Yao, K., Patricelli, G., Deppe, J.L., Krakauer, A.H., Clark, C., Cortopassi, K.A., et al. Acoustic monitoring in terrestrial environments using microphone arrays: applications, technological considerations and prospectus. J. Appl. Ecol. 48:3 (2011), 758–767.
Brandes, T.S., Feature vector selection and use with hidden markov models to identify frequency-modulated bioacoustic signals amidst noise. IEEE Trans. Audio Speech Lang. Process. 16:6 (Aug 2008), 1173–1180.
Del Hoyo, J., Elliott, A., Sargatal, J., Handbook of the Birds of the World. Vol. 7. 2002, Jackamars to Woodpeckers. Lynx, Barcelona.
Dodenhoff, D.J., Stark, R.D., Johnson, E.V., Do woodpecker drums encode information for species recognition?. Condor 103:1 (2001), 143–150.
Florentin, J., Verlinden, O., Autonomous wildlife soundscape recording station using Raspberry Pi. XXIV International Congress on Sound and Vibration (ICSV), 2017 London, UK.
Florentin, J., Dutoit, T., Verlinden, O., Identification of european woodpecker species in audio recordings from their drumming rolls. Ecol. Inform. 35 (2016), 61–70.
Florentin, J., Gérard, M., Turner, K., Rasmont, P., Verlinden, O., Towards a full map of drumming signals in European woodpeckers [abstract]. XXVI International Bioacoustics Congress. Haridwar, India, 2017.
Foote, J., Cooper, M.L., Nam, U., Audio retrieval by rhythmic similarity. Proceedings of the 3rd International Conference on Music Information Retrieval. Paris, France, 2002.
Fox, E.J., Roberts, J.D., Bennamoun, M., Call-independent individual identification in birds. Bioacoustics 18:1 (2008), 51–67.
Fuchs, J., Pons, J.-M., A new classification of the pied woodpeckers assemblage (Dendropicini, Picidae) based on a comprehensive multi-locus phylogeny. Mol. Phylogenet. Evol. 88 (2015), 28–37.
Gorman, G., Woodpeckers of the World; the Complete Guide. 2014, Bloomsbury Publishing.
Grill, T., Schlüter, J., Two convolutional neural networks for bird detection in audio signals. 2017 25th European Signal Processing Conference (EUSIPCO), 2017, IEEE, 1764–1768.
He, K., Zhang, X., Ren, S., Sun, J., Deep residual learning for image recognition. Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2016, 770–778.
Hinton, G., Srivastava, N., Swersky, K., 2012. Lecture 6a: overview of mini-batch gradient descent. In: Neural Networks for Machine Learning. URL https://www.cs.toronto.edu/\textasciitilde{}hinton/nntut.html.
Huang, G., Liu, Z., Van Der Maaten, L., Weinberger, K.Q., Densely connected convolutional networks. Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2017, 4700–4708.
Joly, A., Goëau, H., Botella, C., Glotin, H., Bonnet, P., Vellinga, W.-P., Planqué, R., Müller, H., Overview of lifeclef 2018: A large-scale evaluation of species identification and recommendation algorithms in the era of ai. International Conference of the Cross-Language Evaluation Forum for European Languages, 2018, Springer, 247–266.
Krizhevsky, A., Sutskever, I., Hinton, G.E., Imagenet classification with deep convolutional neural networks. Adv. Neural Inf. Proces. Syst., 2012, 1097–1105.
Laraba, S., Brahimi, M., Tilmanne, J., Dutoit, T., 3d skeleton-based action recognition by representing motion capture sequences as 2d-rgb images. Comp. Animat. Virtual Worlds, 28(3–4), 2017, e1782.
Lartillot, O., Toiviainen, P., A matlab toolbox for musical feature extraction from audio. International Conference on Digital Audio Effects. Bordeaux, France, 2007.
Lasseck, M., Towards automatic large-scale identification of birds in audio recordings. International Conference of the Cross-Language Evaluation Forum for European Languages, 2015, Springer, 364–375.
Lasseck, M., Audio-based bird species identification with deep convolutional neural networks. Working Notes of CLEF, 2018, 2018.
Lu, Y., Lu, F., Sehgal, S., Gupta, S., Du, J., Tham, C.H., Green, P., Wan, V., Multitask learning in connectionist speech recognition. Proceedings of the Australian International Conference on Speech Science and Technology, 2004.
Mikusiński, G., Angelstam, P., Economic geography, forest distribution, and woodpecker diversity in Central Europe. Conserv. Biol. 12:1 (1998), 200–208.
Miles, M.C., Schuppe, E.R., Ligon, R.M. IV, Fuxjager, M.J., Macroevolutionary patterning of woodpecker drums reveals how sexual selection elaborates signals under constraint. Proc. R. Soc. B Biol. Sci., 285(1873), 2018, 20172628.
Pellegrini, T., Densely connected cnns for bird audio detection. Signal Processing Conference (EUSIPCO), 2017 25th European, 2017, IEEE, 1734–1738.
Perktas, U., Barrowclough, G.F., Groth, J.G., Phylogeography and species limits in the green woodpecker complex (Aves: Picidae): multiple Pleistocene refugia and range expansion across europe and the near East. Biol. J. Linn. Soc. 104:3 (2011), 710–723.
Pieretti, N., Farina, A., Morri, D., A new methodology to infer the singing activity of an avian community: The Acoustic Complexity Index (ACI). Ecol. Indic. 11:3 (2011), 868–873.
Pironkov, G., Wood, S.U., Dupont, S., Dutoit, T., Investigating a hybrid learning approach for robust automatic speech recognition. International Conference on Statistical Language and Speech Processing, 2018, Springer, 67–78.
Potamitis, I., Automatic classification of a taxon-rich community recorded in the wild. PLoS One, 9(5), 2014, e96936.
Salamon, J., Bello, J.P., Farnsworth, A., Kelling, S., Fusing shallow and deep learning for bioacoustic bird species classification. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017, IEEE, 141–145.
Schmitz, L., Dumoulin, R., Hybridation des pics vert et cendré (Picus viridis, P. canus) en belgique. Aves 41:1–2 (2004), 91–106.
Sevilla, A., Glotin, H., Audio bird classification with inception-v4 extended with time and time-frequency attention mechanisms. CLEF (Working Notes), 2017.
Simonyan, K., Zisserman, A., Very deep convolutional networks for large-scale image recognition. arXiv, 2014 preprint arXiv:1409.1556.
Sordello, R., Synthèse bibliographique sur les traits de vie du pic cendré (Picus canus, gmelin, 1788) relatifs à ses déplacements et à ses besoins de continuités écologiques. Tech. rep., Service du patrimoine naturel du Muséum national d'Histoire naturelle, 2012.
Stark, R.D., Dodenhoff, D.J., Johnson, E.V., A quantitative analysis of woodpecker drumming. Condor 100:2 (1998), 350–356.
Stowell, D., Plumbley, M.D., Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning. PeerJ, 2, 2014, e488.
Stowell, D., Wood, M.D., Pamuła, H., Stylianou, Y., Glotin, H., Automatic acoustic detection of birds through deep learning: the first bird audio detection challenge. Methods Ecol. Evol. 10:3 (2019), 368–380.
Sueur, J., Farina, A., Ecoacoustics: the ecological investigation and interpretation of environmental sound. Biosemiotics 8:3 (2015), 493–502.
Swiston, K.A., Mennill, D.J., Comparison of manual and automated methods for identifying target sounds in audio recordings of pileated, pale-billed, and putative ivory-billed woodpeckers. J. Field Ornithol. 80:1 (2009), 42–50.
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A., Going deeper with convolutions. Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2015, 1–9.
Turner, K., The case against drumming in middle spotted woodpecker (Dendrocopos medius). Limicola 1 (2011), 37–53.
Winkler, H., Short, L.L., A comparative analysis of acoustical signals in pied woodpeckers (Aves, Picoides). Bull. Am. Mus. Nat. Hist., 160, 1978.
Zabka, H., Zur funktionellen bedeutung der instrumentallaute europäischer spechte unter besonderer berücksichtigung von Dendrocopos major (l.) und d. minor. Mitt. Zool. Mus. Berl. 56:Suppl.: Ann. Orn. 4 (1980), 51–76.
