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Committee Date Time Place Paper Title / Authors Abstract Paper #
IE, CS, IPSJ-AVM [detail] 2023-12-12
13:05		 Fukuoka Kyushu Institute of Technology
(Primary: On-site, Secondary: Online)		 Automatic Classification of Respiratory Diseases Using Multiple Images Generated from Respiratory Sound
Manami Tabata, Huimin Lu, Tohru Kamiya (Kyutech), Shingo Mabu (Yamaguchi Univ.), Shoji Kido (Osaka Univ.) CS2023-90 IE2023-32		 About 8 million people die annually caused to respiratory diseases in the world. Auscultation with a stethoscope is inex... [more] CS2023-90 IE2023-32
pp.43-48
RCS, IT, SIP 2016-01-18
11:50		 Osaka Kwansei Gakuin Univ. Osaka Umeda Campus Abnormal Respiratory Sound Detection for Auscultatory Sound Using Wavelet Transform
Yuka Yokota, Keita Uchida, Masahiro Fukumoto (Kochi Univ. of Tech.) IT2015-62 SIP2015-76 RCS2015-294		 An electronic stethoscope with the recording function of the auscultatory sound has been used in the field of the home-v... [more] IT2015-62 SIP2015-76 RCS2015-294
pp.85-89
PRMU, MI, IE, SIP 2014-05-22
16:20		 Aichi   Signal Processing for Lung-Sound Recognition -- Separation and Classification of Continuous and Discontinuous Adventitious Sounds --
Tomoya Sakai, Takahiro Uchida, Aeri Sakaguchi, Senya Kiyasu (Nagasaki Univ.), Sueharu Miyahara (formerly Nagasaki Univ.), Mikio Oka (Kawasaki Med. Sch.) SIP2014-11 IE2014-11 PRMU2014-11 MI2014-11		 This paper presents signal separation techniques for pattern recognition of lung sounds. From a viewpoint of pattern rec... [more] SIP2014-11 IE2014-11 PRMU2014-11 MI2014-11
pp.55-60
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