Inception-Based Network and Multi-Spectrogram Ensemble Applied To Predict Respiratory Anomalies and Lung Diseases

@article{Pham2021InceptionBasedNA,
  title={Inception-Based Network and Multi-Spectrogram Ensemble Applied To Predict Respiratory Anomalies and Lung Diseases},
  author={Lam Dang Pham and Huy Phan and Ross King and Alfred Mertins and Ian Mcloughlin},
  journal={2021 43rd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
  year={2021},
  pages={253-256}
}
  • L. PhamHuy Phan I. Mcloughlin
  • Published 26 December 2020
  • Computer Science
  • 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
This paper presents an inception-based deep neural network for detecting lung diseases using respiratory sound input. Recordings of respiratory sound collected from patients are first transformed into spectrograms where both spectral and temporal information are well represented, in a process referred to as front-end feature extraction. These spectrograms are then fed into the proposed network, in a process referred to as back-end classification, for detecting whether patients suffer from lung… 

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