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Differentiable fast wavelet transforms in PyTorch with GPU support.
A Discrete Fourier Transform (DFT), a Fast Wavelet Transform (FWT), and a Wavelet Packet Transform (WPT) algorithm in 1-D, 2-D, and 3-D using normalized orthogonal (orthonormal) Haar, Coiflet, Daubechie, Legendre and normalized biorthognal wavelets in Java.
Differentiable and gpu enabled fast wavelet transforms in JAX.
An implementation of the stationary wavelet packet transform on top of PyWavelets
A refactored port and code rebuilt of JWave - Discrete Fourier Transform (DFT), Fast Wavelet Transform (FWT), Wavelet Packet Transform (WPT), some Shifting Wavelet Transform (SWT) by using orthogonal (orthonormal) wavelets like Haar, Daubechie, Coiflet, and other normalized bi-orthogonal wavelets.
Implementation of different texture feature extractors and texture classifiers for both grayscale and RGB images.
🖐️ Course Wavelets: Fingerprint Compression