标题:Insect Sound Recognition Based on Convolutional Neural Network
作者:Dong, Xue ;Yan, Ning ;Wei, Ying
作者机构:[Dong, Xue ;Yan, Ning ;Wei, Ying ] Shandong University, School of Information Science and Engineering, Jinan, China
会议名称:3rd IEEE International Conference on Image, Vision and Computing, ICIVC 2018
会议日期:27 June 2018 through 29 June 2018
来源:2018 3rd IEEE International Conference on Image, Vision and Computing, ICIVC 2018
出版年:2018
页码:855-859
DOI:10.1109/ICIVC.2018.8492871
关键词:Characteristic extraction; Contrast-limit adaptive histogram equalization; Deep learning; Enhanced spectrogram
摘要:A novel insect sound recognition system using enhanced spectrogram and convolutional neural network is proposed. Contrast-limit adaptive histogram equalization (CLAHE) is adopted to enhance R-space spectrogram. Traditionally, artificial feature extraction is an essential step of classification, introducing extra noise caused by subjectivity of individual researchers. In this paper, we construct a convolutional neural network (CNN) as classifier, extracting deep feature by machine learning. Mel-Frequency Cepstral Coefficient (MFCC) and chromatic spectrogram have been compared with enhanced R-space spectrogram as feature image. Eventually, 97.8723 % accuracy rate is achieved among 47 types of insect sound from USDA library. © 2018 IEEE.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056528710&doi=10.1109%2fICIVC.2018.8492871&partnerID=40&md5=b6bfce425a47e0eb0a0169d89b899fa8
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