/Respiratory-Sound-Classification-using-Wavelet-Denoising-and-Deep-Learning-

Leveraged wavelet denoising and deep learning techniques for the classification of respiratory sounds. - Implemented signal processing techniques and wavelet denoising for audio data cleanup and feature extraction. - Developed and trained a deep learning model (Conv1D, Bi-LSTM, CNN, RNN) for phase identification

Primary LanguagePythonMIT LicenseMIT

Respiratory-Sound-Classification-using-Wavelet-Denoising-and-Deep-Learning-

Leveraged wavelet denoising and deep learning techniques for the classification of respiratory sounds. - Implemented signal processing techniques and wavelet denoising for audio data cleanup and feature extraction. - Developed and trained a deep learning model (Conv1D, Bi-LSTM, CNN, RNN) for phase identification