{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T07:51:42Z","timestamp":1769759502273,"version":"3.49.0"},"reference-count":67,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,9,16]],"date-time":"2021-09-16T00:00:00Z","timestamp":1631750400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,9,16]],"date-time":"2021-09-16T00:00:00Z","timestamp":1631750400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["001"],"award-info":[{"award-number":["001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2018\/22482-0"],"award-info":[{"award-number":["2018\/22482-0"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["307411\/2016-8"],"award-info":[{"award-number":["307411\/2016-8"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2022,2]]},"DOI":"10.1007\/s00521-021-06501-w","type":"journal-article","created":{"date-parts":[[2021,9,16]],"date-time":"2021-09-16T03:30:42Z","timestamp":1631763042000},"page":"1923-1937","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A classification and quantification approach to generate features in soundscape ecology using neural networks"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2081-1233","authenticated-orcid":false,"given":"F\u00e1bio Felix","family":"Dias","sequence":"first","affiliation":[]},{"given":"Moacir Antonelli","family":"Ponti","sequence":"additional","affiliation":[]},{"given":"Rosane","family":"Minghim","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,9,16]]},"reference":[{"key":"6501_CR1","unstructured":"Aalborg University (2004) The mel frequency scale and coefficients. http:\/\/kom.aau.dk\/group\/04gr742\/pdf\/MFCC_worksheet.pdf"},{"key":"6501_CR2","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.ecolind.2016.12.018","volume":"75","author":"C Bedoya","year":"2017","unstructured":"Bedoya C, Isaza C, Daza JM, L\u00f3pez JD (2017) Automatic identification of rainfall in acoustic recordings. Ecol Indic 75:95\u2013100","journal-title":"Ecol Indic"},{"key":"6501_CR3","unstructured":"Beijbom O, Hoffman J, Yao E, Darrell T, Rodriguez-Ramirez A, Gonzalez-Rivero M, Guldberg OH (2015) Quantification in-the-wild: data-sets and baselines. arXiv preprint arXiv:1510.04811"},{"key":"6501_CR4","doi-asserted-by":"crossref","unstructured":"Bella A, Ferri C, Hern\u00e1ndez-Orallo J, Ramirez-Quintana MJ (2010). Quantification via probability estimators. In: IEEE international conference on data mining. IEEE, pp 737\u2013742","DOI":"10.1109\/ICDM.2010.75"},{"issue":"8","key":"6501_CR5","doi-asserted-by":"publisher","first-page":"2137","DOI":"10.1890\/07-0004.1","volume":"17","author":"NT Boelman","year":"2007","unstructured":"Boelman NT, Asner GP, Hart PJ, Martin RE (2007) Multi-trophic invasion resistance in hawaii: bioacoustics, field surveys, and airborne remote sensing. Ecol Appl 17(8):2137\u20132144","journal-title":"Ecol Appl"},{"key":"6501_CR6","volume-title":"Online learning and neural networks","author":"L Bottou","year":"1998","unstructured":"Bottou L (1998) Online algorithms and stochastic approximations. In: Saad D (ed) Online learning and neural networks. Cambridge University Press, Cambridge"},{"issue":"10","key":"6501_CR7","doi-asserted-by":"publisher","first-page":"1796","DOI":"10.1111\/2041-210X.13254","volume":"10","author":"T Bradfer-Lawrence","year":"2019","unstructured":"Bradfer-Lawrence T, Gardner N, Bunnefeld L, Bunnefeld N, Willis SG, Dent DH (2019) Guidelines for the use of acoustic indices in environmental research. Methods Ecol Evol 10(10):1796\u20131807","journal-title":"Methods Ecol Evol"},{"issue":"6","key":"6501_CR8","doi-asserted-by":"publisher","first-page":"4640","DOI":"10.1121\/1.4707424","volume":"131","author":"F Briggs","year":"2012","unstructured":"Briggs F, Lakshminarayanan B, Neal L, Fern XZ, Raich R, Hadley SJK, Hadley AS, Betts MG (2012) Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach. J Acoust Soc Am 131(6):4640\u20134650","journal-title":"J Acoust Soc Am"},{"key":"6501_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105501","volume":"81","author":"A Brown","year":"2019","unstructured":"Brown A, Garg S, Montgomery J (2019) Automatic rain and cicada chorus filtering of bird acoustic data. Appl Soft Comput 81:105501","journal-title":"Appl Soft Comput"},{"issue":"6","key":"6501_CR10","doi-asserted-by":"publisher","first-page":"1291","DOI":"10.1109\/TASLP.2017.2690575","volume":"25","author":"E Cak\u0131r","year":"2017","unstructured":"Cak\u0131r E, Parascandolo G, Heittola T, Huttunen H, Virtanen T (2017) Convolutional recurrent neural networks for polyphonic sound event detection. IEEE\/ACM Trans Audio Speech Lang Process 25(6):1291\u20131303","journal-title":"IEEE\/ACM Trans Audio Speech Lang Process"},{"key":"6501_CR11","doi-asserted-by":"crossref","unstructured":"Cavallari GB, Ribeiro LS, Ponti MA (2018). Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis. In: 31st SIBGRAPI conference on graphics, patterns and images (SIBGRAPI). IEEE, pp 440\u2013446","DOI":"10.1109\/SIBGRAPI.2018.00063"},{"key":"6501_CR12","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L (2009) Imagenet: a large-scale hierarchical image database. In: IEEE conference on computer vision and pattern recognition. IEEE, pp 248\u2013255","DOI":"10.1109\/CVPR.2009.5206848"},{"issue":"1","key":"6501_CR13","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.ecolind.2011.05.006","volume":"13","author":"M Depraetere","year":"2012","unstructured":"Depraetere M, Pavoine S, Jiguet F, Gasc A, Duvail S, Sueur J (2012) Monitoring animal diversity using acoustic indices: Implementation in a temperate woodland. Ecol Indic 13(1):46\u201354","journal-title":"Ecol Indic"},{"key":"6501_CR14","doi-asserted-by":"crossref","unstructured":"Dong X, Towsey M, Zhang J, Roe P (2015) Compact features for birdcall retrieval from environmental acoustic recordings. In: Proceedings of the 2015 IEEE 15th international conference on data mining workshops. IEEE Computer Society, pp 1\u20136","DOI":"10.1109\/ICDMW.2015.153"},{"key":"6501_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2020.106929","volume":"120","author":"S Dr\u00f6ge","year":"2021","unstructured":"Dr\u00f6ge S, Martin DA, Andriafanomezantsoa R, Burivalova Z, Fulgence TR, Osen K, Rakotomalala E, Schwab D, Wurz A, Richter T et al (2021) Listening to a changing landscape: acoustic indices reflect bird species richness and plot-scale vegetation structure across different land-use types in north-eastern madagascar. Ecol Indic 120:106929","journal-title":"Ecol Indic"},{"key":"6501_CR16","first-page":"564","volume-title":"European conference on machine learning","author":"G Forman","year":"2005","unstructured":"Forman G (2005) Counting positives accurately despite inaccurate classification. European conference on machine learning. Springer, Berlin, pp 564\u2013575"},{"key":"6501_CR17","doi-asserted-by":"crossref","unstructured":"Gao W, Sebastiani F (2015) Tweet sentiment: from classification to quantification. In: IEEE\/ACM international conference on advances in social networks analysis and mining (ASONAM). IEEE, pp 97\u2013104","DOI":"10.1145\/2808797.2809327"},{"issue":"1","key":"6501_CR18","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s13278-016-0327-z","volume":"6","author":"W Gao","year":"2016","unstructured":"Gao W, Sebastiani F (2016) From classification to quantification in tweet sentiment analysis. Soc Netw Anal Min 6(1):19","journal-title":"Soc Netw Anal Min"},{"issue":"5","key":"6501_CR19","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0065311","volume":"8","author":"A Gasc","year":"2013","unstructured":"Gasc A, Sueur J, Pavoine S, Pellens R, Grandcolas P (2013) Biodiversity sampling using a global acoustic approach: contrasting sites with microendemics in new caledonia. PLoS ONE 8(5):e65311","journal-title":"PLoS ONE"},{"issue":"5","key":"6501_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3117807","volume":"50","author":"P Gonz\u00e1lez","year":"2017","unstructured":"Gonz\u00e1lez P, Casta\u00f1o A, Chawla NV, Coz JJD (2017) A review on quantification learning. ACM Comput Surv (CSUR) 50(5):1\u201340","journal-title":"ACM Comput Surv (CSUR)"},{"issue":"1","key":"6501_CR21","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/s13748-016-0103-3","volume":"6","author":"P Gonz\u00e1lez","year":"2017","unstructured":"Gonz\u00e1lez P, D\u00edez J, Chawla N, del Coz JJ (2017) Why is quantification an interesting learning problem? Prog Artif Intell 6(1):53\u201358","journal-title":"Prog Artif Intell"},{"key":"6501_CR22","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.ins.2012.05.028","volume":"218","author":"V Gonz\u00e1lez-Castro","year":"2013","unstructured":"Gonz\u00e1lez-Castro V, Alaiz-Rodr\u00edguez R, Alegre E (2013) Class distribution estimation based on the hellinger distance. Inf Sci 218:146\u2013164","journal-title":"Inf Sci"},{"key":"6501_CR23","unstructured":"Harvey M (2018) Acoustic detection of humpback whales using a convolutional neural network. https:\/\/ai.googleblog.com\/2018\/10\/acoustic-detection-of-humpback-whales.html"},{"key":"6501_CR24","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"6501_CR25","doi-asserted-by":"publisher","first-page":"107316","DOI":"10.1016\/j.ecolind.2020.107316","volume":"126","author":"LMH Hilasaca","year":"2021","unstructured":"Hilasaca LMH, Gaspar LP, Ribeiro MC, Minghim R (2021) Visualization and categorization of ecological acoustic events based on discriminant features. Ecol Indic 126:107316","journal-title":"Ecol Indic"},{"issue":"1","key":"6501_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-019-0192-5","volume":"6","author":"JM Johnson","year":"2019","unstructured":"Johnson JM, Khoshgoftaar TM (2019) Survey on deep learning with class imbalance. J Big Data 6(1):1\u201354","journal-title":"J Big Data"},{"key":"6501_CR27","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.ecoinf.2012.08.001","volume":"12","author":"EP Kasten","year":"2012","unstructured":"Kasten EP, Gage SH, Fox J, Joo W (2012) The remote environmental assessment laboratory\u2019s acoustic library: an archive for studying soundscape ecology. Ecol Inform 12:50\u201367","journal-title":"Ecol Inform"},{"key":"6501_CR28","unstructured":"Kingma, D.P., Ba, J (2014) Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"6501_CR29","doi-asserted-by":"crossref","unstructured":"Kornblith S, Shlens J, Le QV (2019) Do better imagenet models transfer better? In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 2661\u20132671","DOI":"10.1109\/CVPR.2019.00277"},{"key":"6501_CR30","first-page":"14","volume":"57","author":"B Krause","year":"1987","unstructured":"Krause B (1987) Bioacoustics, habitat ambience in ecological balance. Whole Earth Rev 57:14\u201318","journal-title":"Whole Earth Rev"},{"key":"6501_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoinf.2020.101113","volume":"59","author":"J LeBien","year":"2020","unstructured":"LeBien J, Zhong M, Campos-Cerqueira M, Velev JP, Dodhia R, Ferres JL, Aide TM (2020) A pipeline for identification of bird and frog species in tropical soundscape recordings using a convolutional neural network. Ecol Inform 59:101113","journal-title":"Ecol Inform"},{"issue":"1","key":"6501_CR32","doi-asserted-by":"publisher","first-page":"4547","DOI":"10.1038\/s41598-017-04790-7","volume":"7","author":"TH Lin","year":"2017","unstructured":"Lin TH, Fang SH, Tsao Y (2017) Improving biodiversity assessment via unsupervised separation of biological sounds from long-duration recordings. Sci Rep 7(1):4547","journal-title":"Sci Rep"},{"issue":"3","key":"6501_CR33","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1002\/rse2.141","volume":"6","author":"TH Lin","year":"2020","unstructured":"Lin TH, Tsao Y (2020) Source separation in ecoacoustics: a roadmap towards versatile soundscape information retrieval. Remote Sens Ecol Conserv 6(3):236\u2013247","journal-title":"Remote Sens Ecol Conserv"},{"key":"6501_CR34","first-page":"2579","volume":"9","author":"L van der Maaten","year":"2008","unstructured":"van der Maaten L, Hinton G (2008) Visualizing data using t-SNE. J Mach Learn Res 9:2579\u20132605","journal-title":"J Mach Learn Res"},{"key":"6501_CR35","first-page":"4552","volume":"33","author":"A Maletzke","year":"2019","unstructured":"Maletzke A, dos Reis D, Cherman E, Batista G (2019) Dys: a framework for mixture models in quantification. Proc AAAI Confer Artif Intell 33:4552\u20134560","journal-title":"Proc AAAI Confer Artif Intell"},{"key":"6501_CR36","doi-asserted-by":"crossref","unstructured":"Maletzke AG, dos Reis DM, Batista GE (2017). Quantification in data streams: Initial results. In: Brazilian conference on intelligent systems (BRACIS). IEEE, pp 43\u201348","DOI":"10.1109\/BRACIS.2017.74"},{"key":"6501_CR37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-94989-5","volume-title":"Machine learning: a practical approach on the statistical learning theory","author":"RF Mello","year":"2018","unstructured":"Mello RF, Ponti MA (2018) Machine learning: a practical approach on the statistical learning theory. Springer, Berlin"},{"key":"6501_CR38","doi-asserted-by":"crossref","unstructured":"Mezquida DA, Mart\u00ednez JL (2009) Platform for bee-hives monitoring based on sound analysis. a perpetual warehouse for swarm\u2019s daily activity. Span J Agric Res 7(4):824\u2013828","DOI":"10.5424\/sjar\/2009074-1109"},{"key":"6501_CR39","doi-asserted-by":"publisher","first-page":"106717","DOI":"10.1016\/j.ecolind.2020.106717","volume":"119","author":"SL Mitchell","year":"2020","unstructured":"Mitchell SL, Bicknell JE, Edwards DP, Deere NJ, Bernard H, Davies ZG, Struebig MJ (2020) Spatial replication and habitat context matters for assessments of tropical biodiversity using acoustic indices. Ecol Indic 119:106717","journal-title":"Ecol Indic"},{"issue":"8","key":"6501_CR40","doi-asserted-by":"publisher","first-page":"2650","DOI":"10.1109\/TVCG.2018.2846735","volume":"25","author":"LG Nonato","year":"2018","unstructured":"Nonato LG, Aupetit M (2018) Multidimensional projection for visual analytics: linking techniques with distortions, tasks, and layout enrichment. IEEE Trans Vis Comput Graph 25(8):2650\u20132673","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"6501_CR41","doi-asserted-by":"crossref","unstructured":"Parascandolo G, Huttunen H, Virtanen T (2016) Recurrent neural networks for polyphonic sound event detection in real life recordings. In: IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 6440\u20136444","DOI":"10.1109\/ICASSP.2016.7472917"},{"key":"6501_CR42","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.ecoinf.2013.11.003","volume":"21","author":"SE Parks","year":"2014","unstructured":"Parks SE, Miksis-Olds JL, Denes SL (2014) Assessing marine ecosystem acoustic diversity across ocean basins. Ecol Inform 21:81\u201388","journal-title":"Ecol Inform"},{"issue":"10","key":"6501_CR43","doi-asserted-by":"publisher","first-page":"1513","DOI":"10.1007\/s10980-012-9806-4","volume":"27","author":"B Pekin","year":"2012","unstructured":"Pekin B, Jung J, Villanueva-Rivera L, Pijanowski B, Ahumada J (2012) Modeling acoustic diversity using soundscape recordings and lidar-derived metrics of vertical forest structure in aneotropical rainforest. Landsc Ecol 27(10):1513\u20131522","journal-title":"Landsc Ecol"},{"key":"6501_CR44","unstructured":"Perez, L., Wang, J (2017) The effectiveness of data augmentation in image classification using deep learning. arXiv preprint arXiv:1712.04621"},{"issue":"3","key":"6501_CR45","doi-asserted-by":"publisher","first-page":"868","DOI":"10.1016\/j.ecolind.2010.11.005","volume":"11","author":"N Pieretti","year":"2011","unstructured":"Pieretti N, Farina A, Morri D (2011) A new methodology to infer the singing activity of an avian community: the Acoustic Complexity Index (ACI). Ecol Indic 11(3):868\u2013873","journal-title":"Ecol Indic"},{"issue":"9","key":"6501_CR46","doi-asserted-by":"publisher","first-page":"1213","DOI":"10.1007\/s10980-011-9600-8","volume":"26","author":"BC Pijanowski","year":"2011","unstructured":"Pijanowski BC, Farina A, Gage SH, Dumyahn SL, Krause BL (2011) What is soundscape ecology? An introduction and overview of an emerging new science. Landsc Ecol 26(9):1213\u20131232","journal-title":"Landsc Ecol"},{"key":"6501_CR47","doi-asserted-by":"crossref","unstructured":"Ponti M.A, Ribeiro L.S.F, Nazare T.S, Bui T, Collomosse J (2017) Everything you wanted to know about deep learning for computer vision but were afraid to ask. In: SIBGRAPI-conference on graphics, patterns and images. Brazilian Computer Society (SBC)","DOI":"10.1109\/SIBGRAPI-T.2017.12"},{"key":"6501_CR48","doi-asserted-by":"crossref","unstructured":"Ramsay JO (2006) Functional data analysis. Wiley Online Library","DOI":"10.1002\/0471667196.ess3138"},{"issue":"1","key":"6501_CR49","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1080\/14888386.2019.1696229","volume":"21","author":"R Righini","year":"2020","unstructured":"Righini R, Pavan G (2020) A soundscape assessment of the sasso fratino integral nature reserve in the central apennines, italy. Biodiversity 21(1):4\u201314","journal-title":"Biodiversity"},{"key":"6501_CR50","doi-asserted-by":"crossref","unstructured":"Salamon J, Bello JP (2015). Unsupervised feature learning for urban sound classification. In: IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 171\u2013175","DOI":"10.1109\/ICASSP.2015.7177954"},{"issue":"3","key":"6501_CR51","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1109\/LSP.2017.2657381","volume":"24","author":"J Salamon","year":"2017","unstructured":"Salamon J, Bello JP (2017) Deep convolutional neural networks and data augmentation for environmental sound classification. IEEE Signal Process Lett 24(3):279\u2013283","journal-title":"IEEE Signal Process Lett"},{"issue":"1","key":"6501_CR52","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.marpolbul.2016.02.055","volume":"105","author":"I S\u00e1nchez-Gendriz","year":"2016","unstructured":"S\u00e1nchez-Gendriz I, Padovese L (2016) Underwater soundscape of marine protected areas in the south Brazilian coast. Mar Pollut Bull 105(1):65\u201372","journal-title":"Mar Pollut Bull"},{"key":"6501_CR53","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2020.107050","volume":"121","author":"MD Scarpelli","year":"2021","unstructured":"Scarpelli MD, Ribeiro MC, Teixeira CP (2021) What does atlantic forest soundscapes can tell us about landscape? Ecol Indicat 121:107050","journal-title":"Ecol Indicat"},{"key":"6501_CR54","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2019.135403","volume":"707","author":"MD Scarpelli","year":"2020","unstructured":"Scarpelli MD, Ribeiro MC, Teixeira FZ, Young RJ, Teixeira CP (2020) Gaps in terrestrial soundscape research: it\u2019s time to focus on tropical wildlife. Sci Total Environ 707:135403","journal-title":"Sci Total Environ"},{"key":"6501_CR55","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1126\/science.343.6173.834","volume":"343","author":"K Servick","year":"2014","unstructured":"Servick K (2014) Eavesdropping on ecosystems. Science 343:834\u2013837","journal-title":"Science"},{"issue":"1","key":"6501_CR56","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R (2014) Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res 15(1):1929\u20131958","journal-title":"J Mach Learn Res"},{"key":"6501_CR57","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.488","volume":"2","author":"D Stowell","year":"2014","unstructured":"Stowell D, Plumbley MD (2014) Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning. PeerJ 2:e488","journal-title":"PeerJ"},{"key":"6501_CR58","doi-asserted-by":"crossref","unstructured":"Strout J, Rogan B, Seyednezhad SM, Smart K, Bush M, Ribeiro E (2017) Anuran call classification with deep learning. In: IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 2662\u20132665","DOI":"10.1109\/ICASSP.2017.7952639"},{"issue":"2","key":"6501_CR59","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1080\/09524622.2008.9753600","volume":"18","author":"J Sueur","year":"2008","unstructured":"Sueur J, Aubin T, Simonis C (2008) Seewave, a free modular tool for sound analysis and synthesis. Bioacoustics 18(2):213\u2013226","journal-title":"Bioacoustics"},{"issue":"4","key":"6501_CR60","doi-asserted-by":"publisher","first-page":"772","DOI":"10.3813\/AAA.918757","volume":"100","author":"J Sueur","year":"2014","unstructured":"Sueur J, Farina A, Gasc A, Pieretti N, Pavoine S (2014) Acoustic indices for biodiversity assessment and landscape investigation. Acta Acust United Acust 100(4):772\u2013781","journal-title":"Acta Acust United Acust"},{"issue":"12","key":"6501_CR61","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0004065","volume":"3","author":"J Sueur","year":"2008","unstructured":"Sueur J, Pavoine S, Hamerlynck O, Duvail S (2008) Rapid acoustic survey for biodiversity appraisal. PLoS ONE 3(12):e4065","journal-title":"PLoS ONE"},{"key":"6501_CR62","volume-title":"Introduction to data mining","author":"PN Tan","year":"2005","unstructured":"Tan PN, Steinbach M, Kumar V (2005) Introduction to data mining, 1st edn. Pearson Education India, Noida","edition":"1"},{"issue":"4","key":"6501_CR63","doi-asserted-by":"publisher","first-page":"150","DOI":"10.3390\/jrfm7040150","volume":"7","author":"D Tasche","year":"2014","unstructured":"Tasche D (2014) Exact fit of simple finite mixture models. J Risk Financ Manag 7(4):150\u2013164","journal-title":"J Risk Financ Manag"},{"key":"6501_CR64","first-page":"290","volume-title":"Joint European conference on machine learning and knowledge discovery in databases","author":"M Thomas","year":"2019","unstructured":"Thomas M, Martin B, Kowarski K, Gaudet B, Matwin S (2019) Marine mammal species classification using convolutional neural networks and a novel acoustic representation. Joint European conference on machine learning and knowledge discovery in databases. Springer, Berlin, pp 290\u2013305"},{"key":"6501_CR65","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.ecoinf.2013.11.007","volume":"21","author":"M Towsey","year":"2014","unstructured":"Towsey M, Wimmer J, Williamson I, Roe P (2014) The use of acoustic indices to determine avian species richness in audio-recordings of the environment. Ecol Inform 21:110\u2013119","journal-title":"Ecol Inform"},{"issue":"9","key":"6501_CR66","doi-asserted-by":"publisher","first-page":"1233","DOI":"10.1007\/s10980-011-9636-9","volume":"26","author":"L Villanueva-Rivera","year":"2011","unstructured":"Villanueva-Rivera L, Pijanowski B, Doucette J, Pekin B (2011) A primer of acoustic analysis for landscape ecologists. Landsc Ecol 26(9):1233\u20131246","journal-title":"Landsc Ecol"},{"issue":"2","key":"6501_CR67","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1109\/TAU.1967.1161901","volume":"15","author":"P Welch","year":"1967","unstructured":"Welch P (1967) The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust 15(2):70\u201373","journal-title":"IEEE Trans Audio Electroacoust"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06501-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-021-06501-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06501-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T15:07:13Z","timestamp":1675696033000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-021-06501-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,16]]},"references-count":67,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,2]]}},"alternative-id":["6501"],"URL":"https:\/\/doi.org\/10.1007\/s00521-021-06501-w","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,16]]},"assertion":[{"value":"1 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}