K. Lambert and P. G. Mcdonald, A low-cost, yet simple and highly repeatable system for acoustically surveying cryptic species, Austral Ecology, vol.39, issue.7, 2014.

V. Lostanlen, J. Salamon, A. Farnsworth, S. Kelling, and J. P. Bello, BirdVox-full-night: a dataset and benchmark for avian flight call detection, Proceedings of the IEEE ICASSP, 2018.

D. Luther, Signaller: receiver coordination and the timing of communication in Amazonian birds, Biology Letters, vol.4, 2008.

D. Luther and R. Wiley, Production and perception of communicatory signals in a noisy environment, Biology Letters, vol.5, 2009.

T. A. Marques, L. Thomas, S. W. Martin, D. K. Mellinger, J. A. Ward et al., Estimating animal population density using passive acoustics, Biological Reviews, vol.88, issue.2, pp.287-309, 2012.

V. Morfi and D. Stowell, Data-efficient weakly supervised learning for low-resource audio event detection using deep learning, Proceedings of the detection and classification of acoustic scenes and, pp.123-127, 2018.

V. Morfi and D. Stowell, Deep learning for audio event detection and tagging on lowresource datasets, Applied Sciences, vol.8, issue.8, 2018.

V. Morfi, D. Stowell, and H. Pamu?a, Transcriptions of NIPS4B 2013 bird challenge training dataset, 2018.

K. Pacifici, T. R. Simons, and K. H. Pollock, Effects of vegetation and background noise on the detection process in auditory avian point-count surveys, The Auk, vol.125, issue.4, 2008.

T. Pellegrini, Densely connected CNNs for bird audio detection, 2017 25th European Signal Processing Conference (EUSIPCO, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01913975

V. Roger, M. Bartcus, F. Chamroukhi, and H. Glotin, Unsupervised bioacoustic segmentation by hierarchical Dirichlet process hidden Markov model, Multimedia tools and applications for environmental & biodiversity informatics, pp.113-130, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01879385

J. F. Ruiz-muñoz, M. Orozco-alzate, and G. Castellanos-dominguez, Multiple instance learning-based birdsong classification using unsupervised recording segmentation, Proceedings of the 24th International Conference on Artificial Intelligence, IJCAI'15, pp.2632-2638, 2015.

J. Salamon and J. P. Bello, Deep convolutional neural networks and data augmentation for environmental sound classification, IEEE Signal Processing Letters, vol.24, pp.279-283, 2017.

J. Schlüter, Learning to pinpoint singing voice from weakly labeled examples, Proceedings of the 17th international society for music information retrieval conference, 2016.

S. G. Sovern, E. D. Forsman, G. S. Olson, B. L. Biswell, M. Taylor et al., Barred owls and landscape attributes influence territory occupancy of northern spotted owls, The Journal of Wildlife Management, vol.78, issue.8, 2014.