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1. Optimal_Scalogram Optimal_Scalogram Public

   To reduce computational complexity in deep learning-based acoustic recognition, this approach utilizes downsampled scalograms and shortened wavelet kernel lengths.

   Jupyter Notebook 1

2. Comparison-Performance-of-Spectrogram-and-Scalogram-as-Input-of-Acoustic-Recognition-Task Comparison-Performance-of-Spectrogram-and-Scalogram-as-Input-of-Acoustic-Recognition-Task Public

   This notebook includes source codes used for development of the research named as the title. Below is the end-to-end steps for processing audio data and perform recognition task.

   Jupyter Notebook

3. Continuous-Wavelet-Transform-in-Acoustic-Recognition-Using-Hop-Size Continuous-Wavelet-Transform-in-Acoustic-Recognition-Using-Hop-Size Public

   Reduce Computational Complexity for Continuous Wavelet Transform in Acoustic Recognition Using Hop Size

   Jupyter Notebook

4. pywt pywt Public

   Forked from PyWavelets/pywt

   PyWavelets - Wavelet Transforms in Python

   Python