PyTorchWavelets
by tomrunia
PyTorch implementation of the wavelet analysis from Torrence & Compo (1998)
AI summary
Wavelet processor
PyTorch implementation of wavelet analysis for signal processing
- stars
- 307
- forks
- 60
- watching
- 11
Similar projects
Found by comparing what the projects do, not just their names.
YOLO detector
A PyTorch implementation of the YOLO (You Only Look Once) v2 object detection algorithm with flexible configuration and parallel training capabilities.
Wave solver
A Python package for solving the wave equation using recurrent neural networks and automatic differentiation.
Segmentation toolkit
Provides PyTorch implementations of deep learning models for semantic segmentation
Spatiotemporal data processor
A comprehensive library for processing spatiotemporal data with PyTorch
MobileNetV3 optimizer
An implementation of MobileNetV3 using PyTorch with search space optimization
QANet impl
An implementation of QANet with PyTorch for text classification tasks
Time Series Analyzer
A Python package for time series classification and analysis
Audio processor
An audio processing toolkit using PyTorch convolutional neural networks to generate spectrograms from raw audio data
CNN model
An implementation of a lightweight convolutional neural network architecture for mobile devices
Neural net trainer
A PyTorch framework simplifying neural network training with automated boilerplate code and callback utilities
Image upscaler
A PyTorch implementation of an image super-resolution model based on dense skip connections.
Scattering algorithm
A software package implementing a deep learning-based image feature extraction technique using the scattering transform
Neural net architecture
A PyTorch implementation of a ShuffleNet-v2 neural network architecture for image classification.
pytorch/tnt1.7K
PyTorch toolkit
A collection of tools and utilities for building and training neural networks with PyTorch.
Computer Vision Toolkit
A PyTorch toolbox for supporting research and development of domain adaptation, generalization, and semi-supervised learning methods in computer vision.
