Interfacing Kymatio into deep learning frameworks allows the programmer to backpropagate the gradient of wavelet scattering coefficients, thus integrating them within an end-to-end trainable pipeline, such as a deep neural network. Portability
Wavelet scattering transforms in Python with GPU acceleration deep-learningtensorflownumpyscikit-learnkeraspytorchwaveletsscattering-transform UpdatedJan 28, 2025 Python ar1st0crat/NWaves Star479 Code Issues Pull requests Discussions .NET DSP library with a lot of audio processing functions ...
论文研究-Performance evaluation of wavelet scattering network in image texture classification in various color spaces.pdf 小波散射网络在各种彩色空间进行图像纹理分类的比较研究,伍家松,姜龙玉,图像纹理在图像分析各种应用中具有重要作用。本文在各种彩色空间对小波散射网络在彩色图像纹理分类中的性能进行了比较研究。在...
We used Python 3.7 to implement the NN classifier. 4.1. Feature Extraction We used the Gabor wavelets to perform wavelet decomposition. The corresponding low-pass filter ϕ is a Gaussian function. We set the invariance scale to 0.5 second. The constructed wavelet scattering network includes two...
Hybrid scattering-LSTM networks for automated detection of sleep arousals. Physiol. Meas. 2019, 40, 074001. [Google Scholar] [CrossRef] [PubMed] Bao, W.; Yue, J.; Rao, Y. A deep learning framework for financial time series using stacked autoencoders and long-short term memory. PLoS ...
However, due to atmospheric influences, the complexity of water quality parameters, surface scattering, and aquatic plants, the satellite remote sensing characteristics of water cannot be used to directly determine water quality parameters, which makes it extremely challenging to implement regional water ...