Using Back-Propagation Neural Network for Automatic Wheezing Detection

doi:10.1109/IIH-MSP.2015.51

完整後設資料紀錄

DC 欄位	值	語言
dc.contributor.author	Lin, Bor-Shing	en_US
dc.contributor.author	Jan, Gene Eu	en_US
dc.contributor.author	Wu, Huey-Dong	en_US
dc.contributor.author	Lin, Bor-Shyh	en_US
dc.contributor.author	Chen, Sao-Jie	en_US
dc.date.accessioned	2017-04-21T06:49:49Z	-
dc.date.available	2017-04-21T06:49:49Z	-
dc.date.issued	2015	en_US
dc.identifier.isbn	978-0-7695-5668-0	en_US
dc.identifier.uri	http://dx.doi.org/10.1109/IIH-MSP.2015.51	en_US
dc.identifier.uri	http://hdl.handle.net/11536/135579	-
dc.description.abstract	This study describes the design of a fast and high performance wheeze recognition system. The proposed wheezing detection algorithm is based on order truncate average (OTA) and back-propagation neural network (BPNN). Some features are then extracted from the processed spectra to train a BPNN. Eventually, the new testing samples go through the trained BPNN to recognize whether they are wheezing sounds. Experimental results show a high sensitivity of 0.946 and a specificity of 1.0 in qualitative analysis of wheeze recognition.	en_US
dc.language.iso	en_US	en_US
dc.subject	asthma	en_US
dc.subject	wheezing detection	en_US
dc.subject	bilateral filtering	en_US
dc.subject	order truncate average	en_US
dc.subject	back-propagation neural network	en_US
dc.title	Using Back-Propagation Neural Network for Automatic Wheezing Detection	en_US
dc.type	Proceedings Paper	en_US
dc.identifier.doi	10.1109/IIH-MSP.2015.51	en_US
dc.identifier.journal	2015 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING (IIH-MSP)	en_US
dc.citation.spage	49	en_US
dc.citation.epage	52	en_US
dc.contributor.department	影像與生醫光電研究所	zh_TW
dc.contributor.department	Institute of Imaging and Biomedical Photonics	en_US
dc.identifier.wosnumber	WOS:000375671900013	en_US
dc.citation.woscount	0	en_US
顯示於類別：	會議論文