{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T22:41:11Z","timestamp":1773528071704,"version":"3.50.1"},"publisher-location":"New York, New York, USA","reference-count":23,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1145\/2948992.2949016","type":"proceedings-article","created":{"date-parts":[[2016,7,25]],"date-time":"2016-07-25T15:17:25Z","timestamp":1469459845000},"page":"73-78","source":"Crossref","is-referenced-by-count":28,"title":["Automatic Classification of Anuran Sounds Using Convolutional Neural Networks"],"prefix":"10.1145","author":[{"given":"Juan","family":"Colonna","sequence":"first","affiliation":[{"name":"Universidade Federal do Amazonas, Manaus, Brazil"}]},{"given":"Tanel","family":"Peet","sequence":"additional","affiliation":[{"name":"Estonian Information Technology College, Tallinn, Estonia"}]},{"given":"Carlos Abreu","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Instituto Politecnico do Porto, Porto, Portugal"}]},{"given":"Al\u00edpio M.","family":"Jorge","sequence":"additional","affiliation":[{"name":"Universidade do Porto, Porto, Portugal"}]},{"given":"Elsa Ferreira","family":"Gomes","sequence":"additional","affiliation":[{"name":"Instituto Superior de Engenharia do Porto, Porto, Portugal"}]},{"given":"Jo\u00e3o","family":"Gama","sequence":"additional","affiliation":[{"name":"Universidade do Porto, Porto, Portugal"}]}],"member":"320","reference":[{"key":"key-10.1145\/2948992.2949016-1","doi-asserted-by":"crossref","unstructured":"I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. Wireless sensor networks: a survey. Computer networks, 38(4):393--422, 2002.","DOI":"10.1016\/S1389-1286(01)00302-4"},{"key":"key-10.1145\/2948992.2949016-2","doi-asserted-by":"crossref","unstructured":"J. Cai, D. Ee, B. Pham, P. Roe, and J. Zhang. Sensor network for the monitoring of ecosystem: Bird species recognition. In Intelligent Sensors, Sensor Networks and Information, 2007. ISSNIP 2007. 3rd International Conference on, pages 293--298. IEEE, 2007.","DOI":"10.1109\/ISSNIP.2007.4496859"},{"key":"key-10.1145\/2948992.2949016-3","doi-asserted-by":"crossref","unstructured":"C. Carey, W. R. Heyer, J. Wilkinson, R. A. Alford, J. W. Arntzen, T. Halliday, L. Hungerford, K. R. Lips, E. M. Middleton, S. A. Orchard, and A. S. Rand. Amphibian declines and environmental change: Use of remote-sensing data to identify environmental correlates. Conservation Biology, 15(4):903--913, 2001.","DOI":"10.1046\/j.1523-1739.2001.015004903.x"},{"key":"key-10.1145\/2948992.2949016-4","doi-asserted-by":"crossref","unstructured":"J. P. Collins and A. Storfer. Global amphibian declines: sorting the hypotheses. Diversity and distributions, 9(2):89--98, 2003.","DOI":"10.1046\/j.1472-4642.2003.00012.x"},{"key":"key-10.1145\/2948992.2949016-5","doi-asserted-by":"crossref","unstructured":"J. G. Colonna, A. D. Ribas, E. M. dos Santos, and E. F. Nakamura. Feature subset selection for automatically classifying anuran calls using sensor networks. In Neural Networks (IJCNN), The 2012 International Joint Conference on, pages 1--8, June 2012.","DOI":"10.1109\/IJCNN.2012.6252794"},{"key":"key-10.1145\/2948992.2949016-6","doi-asserted-by":"crossref","unstructured":"S. B. Davis and P. Mermelstein. Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. Acoustics, Speech and Signal Processing, IEEE Transactions on, 28(4):357--366, 1980.","DOI":"10.1109\/TASSP.1980.1163420"},{"key":"key-10.1145\/2948992.2949016-7","unstructured":"I. De la Riva, S. Reichle, J. K&#246;hler, S. L&#246;tters, J. Bosch, S. Mayer, A. Hennessey, and J. Padial. Sounds of frogs and toads of bolivia, 2002."},{"key":"key-10.1145\/2948992.2949016-8","doi-asserted-by":"crossref","unstructured":"A. G. de Oliveira, T. M. Ventura, T. D. Ganchev, J. M. de Figueiredo, O. Jahn, M. I. Marques, and K.-L. Schuchmann. Bird acoustic activity detection based on morphological filtering of the spectrogram. Applied Acoustics, 98:34--42, 2015.","DOI":"10.1016\/j.apacoust.2015.04.014"},{"key":"key-10.1145\/2948992.2949016-9","unstructured":"G. Grigg, A. Taylor, H. Mc Callum, and G. Watson. Monitoring frog communities: an application of machine learning. In Proceedings of Eighth Innovative Applications of Artificial Intelligence Conference, Portland Oregon, pages 1564--1569, 1996."},{"key":"key-10.1145\/2948992.2949016-10","unstructured":"C. Haddad, J. Giovanelli, L. Giasson, and L. Toledo. Guia sonoro dos anf&#237;bios anuros da mata atl&#226;ntica. Commercial digital media. Manaus: NovoDisc M&#237;dia Digital da Amaz&#244;nia Ltda, 2005."},{"key":"key-10.1145\/2948992.2949016-11","doi-asserted-by":"crossref","unstructured":"W. Hu, N. Bulusu, C. T. Chou, S. Jha, A. Taylor, and V. N. Tran. Design and evaluation of a hybrid sensor network for cane toad monitoring. ACM Transactions on Sensor Networks (TOSN), 5(1):4, 2009.","DOI":"10.1145\/1464420.1464424"},{"key":"key-10.1145\/2948992.2949016-12","doi-asserted-by":"crossref","unstructured":"C.-J. Huang, Y.-J. Yang, D.-X. Yang, and Y.-J. Chen. Frog classification using machine learning techniques. Expert Systems with Applications, 36(2, Part 2):3737--3743, 2009.","DOI":"10.1016\/j.eswa.2008.02.059"},{"key":"key-10.1145\/2948992.2949016-13","doi-asserted-by":"crossref","unstructured":"E. J. Humphrey, J. P. Bello, and Y. LeCun. Feature learning and deep architectures: new directions for music informatics. Journal of Intelligent Information Systems, 41(3):461--481, 2013.","DOI":"10.1007\/s10844-013-0248-5"},{"key":"key-10.1145\/2948992.2949016-14","unstructured":"B. Logan et al. Mel frequency cepstral coefficients for music modeling. In ISMIR, 2000."},{"key":"key-10.1145\/2948992.2949016-15","unstructured":"R. Loughran, J. Walker, M. O'Neill, and M. O'Farrell. The use of mel-frequency cepstral coefficients in musical instrument identification. In International Computer Music Conference, Belfast, Northern Ireland. Citeseer, 2008."},{"key":"key-10.1145\/2948992.2949016-16","unstructured":"I. G. Maglogiannis. Emerging artificial intelligence applications in computer engineering: real word AI systems with applications in eHealth, HCI, information retrieval and pervasive technologies, volume 160. Ios Press, 2007."},{"key":"key-10.1145\/2948992.2949016-17","unstructured":"C. Marty and P. Gaucher. Sound guide to the tailless amphibians of French Guiana. CEBA, 1999."},{"key":"key-10.1145\/2948992.2949016-18","doi-asserted-by":"crossref","unstructured":"M. Matsugu, K. Mori, Y. Mitari, and Y. Kaneda. Subject independent facial expression recognition with robust face detection using a convolutional neural network. Neural Networks, 16(5-6):555--559, 2003. Advances in Neural Networks Research: IJCNN '03.","DOI":"10.1016\/S0893-6080(03)00115-1"},{"key":"key-10.1145\/2948992.2949016-19","unstructured":"P. Mermelstein. Distance measures for speech recognition, psychological and instrumental. Pattern recognition and artificial intelligence, 116:374--388, 1976."},{"key":"key-10.1145\/2948992.2949016-20","doi-asserted-by":"crossref","unstructured":"I. Potamitis. Automatic classification of a taxon-rich community recorded in the wild. PloS one, 9(5):e96936, 2014.","DOI":"10.1371\/journal.pone.0096936"},{"key":"key-10.1145\/2948992.2949016-21","doi-asserted-by":"crossref","unstructured":"G. Vaca-Castano and D. Rodriguez. Using syllabic mel cepstrum features and k-nearest neighbors to identify anurans and birds species. In Signal Processing Systems (SIPS), 2010 IEEE Workshop on, pages 466--471. IEEE, 2010.","DOI":"10.1109\/SIPS.2010.5624892"},{"key":"key-10.1145\/2948992.2949016-22","doi-asserted-by":"crossref","unstructured":"G. Xing, X. Wang, Y. Zhang, C. Lu, R. Pless, and C. Gill. Integrated coverage and connectivity configuration for energy conservation in sensor networks. ACM Transactions on Sensor Networks (TOSN), 1(1):36--72, 2005.","DOI":"10.1145\/1077391.1077394"},{"key":"key-10.1145\/2948992.2949016-23","doi-asserted-by":"crossref","unstructured":"G. G. Yen and Q. Fu. Automatic frog call monitoring system: a machine learning approach. In AeroSense 2002, pages 188--199. International Society for Optics and Photonics, 2002.","DOI":"10.1117\/12.458716"}],"event":{"name":"the Ninth International C* Conference","location":"Porto, Portugal","acronym":"C3S2E '16","number":"9","sponsor":["BytePress","ISEP"],"start":{"date-parts":[[2016,7,20]]},"end":{"date-parts":[[2016,7,22]]}},"container-title":["Proceedings of the Ninth International C* Conference on Computer Science &amp; Software Engineering - C3S2E '16"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2948992.2949016","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=2949016&amp;ftid=1766662&amp;dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:55:59Z","timestamp":1750222559000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=2948992.2949016"}},"subtitle":[],"proceedings-subject":"Computer Science & Software Engineering","short-title":[],"issued":{"date-parts":[[2016]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1145\/2948992.2949016","relation":{},"subject":[],"published":{"date-parts":[[2016]]}}}