{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T10:29:19Z","timestamp":1757586559218},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,9,15]]},"abstract":"<jats:p>In this paper, a classification of mosquito\u2019s specie is performed using mosquito wingbeats samples obtained by optical sensor. Six world-wide representative species of mosquitos, which are Aedes aegypti, Aedes albopictus, Anopheles arabiensis, Anopheles gambiae and Culex pipiens, Culex quinquefasciatus, are considered for classification. A total of 60,000 samples are divided equally in each specie mentioned above. In total, 25 audio feature extraction algorithms are applied to extract 39 feature values per sample. Further, each audio feature is transformed to a color image, which shows audio features presenting by different pixel values. We used a fully connected neural networks for audio features and a convolutional neural network (CNN) for image dataset generated from audio features. The CNN-based classifier shows 90.75% accuracy, which outperforms the accuracy of 87.18% obtained by the first classifier using directly audio features.<\/jats:p>","DOI":"10.3233\/faia200559","type":"book-chapter","created":{"date-parts":[[2020,9,16]],"date-time":"2020-09-16T23:01:50Z","timestamp":1600297310000},"source":"Crossref","is-referenced-by-count":3,"title":["A CNN-Based Mosquito Classification Using Image Transformation of Wingbeat Features"],"prefix":"10.3233","author":[{"given":"Jose Alvaro","family":"Luna-Gonzalez","sequence":"first","affiliation":[{"name":"Graduate Section, Instituto Polit\u00e9cnico Nacional, Mexico City, Mexico"}]},{"given":"Daniel","family":"Robles-Camarillo","sequence":"additional","affiliation":[{"name":"Universidad Politecnico de Pachuca, Hidalgo, Mexico"}]},{"given":"Mariko","family":"Nakano-Miyatake","sequence":"additional","affiliation":[{"name":"Graduate Section, Instituto Polit\u00e9cnico Nacional, Mexico City, Mexico"}]},{"given":"Humberto","family":"Lanz-Mendoza","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Salud P\u00fablica, Morelos, Mexico"}]},{"given":"Hector","family":"Perez-Meana","sequence":"additional","affiliation":[{"name":"Graduate Section, Instituto Polit\u00e9cnico Nacional, Mexico City, Mexico"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Knowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"http:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA200559","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,17]],"date-time":"2020-09-17T13:34:45Z","timestamp":1600349685000},"score":1,"resource":{"primary":{"URL":"http:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA200559"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,15]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia200559","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,15]]}}}