🔥🔥A pytorch implementation of Dynamic Convolutional Layer in Dynamic Conditional Convolutional Network for Few-Shot Learning🔥🔥
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Updated
Dec 9, 2021 - Python
🔥🔥A pytorch implementation of Dynamic Convolutional Layer in Dynamic Conditional Convolutional Network for Few-Shot Learning🔥🔥
Standards-conformant acoustics library for Python: measurement and metrology, building, environmental and room acoustics, psychoacoustics, electroacoustics, vibration, underwater and aircraft/rotorcraft noise. Every method is implemented from the standard and validated against reference data, with teaching-style docs (formerly PyOctaveBand).
A librosa STFT/Fbank/mfcc feature extration written up in PyTorch using 1D Convolutions.
Python code for generating Leung-Malik (LM) filter bank that is typically used in texture analysis and classification.
Implements High-Gamma dataset decoding using Filter Bank Common Spatial Pattern with rLDA classification and Neural Networks.
Web Audio high quality spectogram from biquad bandpass filters
Transparent CPU reproduction of filter-bank TRCA and eTRCA for 40-class SSVEP recognition
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