Energy-Efficient Intelligent Pulmonary Auscultation for Post COVID-19 Era Wearable Monitoring Enabled by Two-Stage Hybrid Neural Network-Reference-Cited by-同舟云学术

Energy-Efficient Intelligent Pulmonary Auscultation for Post COVID-19 Era Wearable Monitoring Enabled by Two-Stage Hybrid Neural Network

Published:2022-05-28 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Symposium on Circuits and Systems (ISCAS)
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Author:

Liu Bingqiang¹,Wen Ziyuan¹,Zhu Hongling²,Lai Jinsheng²,Wu Jiajun¹,Ping Heng¹,Liu Wenqing³,Yu Guoyi¹,Zhang Jianmin³,Liu Zuozhu⁴,Zeng Hesong²,Wang Chao¹

Affiliation:

1. Huazhong University of Science and Technology,School of Optical and Electronic Information,Wuhan,China

2. Huazhong University of Science and Technology,Tongji Medical College,Wuhan,China

3. Jianghan University,School of Artificial Intelligence,Wuhan,China

4. Zhejiang University - University of Illinois at Urbana-Champaign Institute, Zhejiang University,Hangzhou,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9937201/9937203/09937985.pdf?arnumber=9937985

Reference32 articles.

1. MobileNetV2: Inverted Residuals and Linear Bottlenecks

2. Adaptive Noise Suppression of Pediatric Lung Auscultations With Real Applications to Noisy Clinical Settings in Developing Countries

3. Acoustic Methods for Pulmonary Diagnosis

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