Up-sampling and denoising signals using a deep neural network model
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Updated
Jun 1, 2024 - Python
Up-sampling and denoising signals using a deep neural network model
Easily run SqueezeLite with Alsa or PulseAudio output with Docker. Bluetooth support. Upsampling 2x 4x 8x with "Goldilocks" settings by Archimago
GUI application for Anime4K shaders which allows to save upscaled video to disk
A cubic spline interpolation implementation that returns cubic polynomial coefficients for each segment of inputs.
Dive into the world of Signal and Image Processing with this repository. Explore a collection of Python programs covering Discrete Fourier Transform, Elementary Signals, Sampling, Point Processing Techniques, Histogram Processing, Frequency Domain Filtering, Edge Detection, Erosion and Dilation, and Morphological Operations.
Easily run mpd with Alsa or PulseAudio output with Docker. Upsampling 2x 4x 8x with "Goldilocks" settings by Archimago. Scrobbling support.
A project on Image Processing, leveraging PyQt5 for a user-friendly GUI and implementing essential operations like Low Pass Filter, Downsampling, Upsampling, Thresholding, and Negative Image Generation. It offers a visually engaging experience while exploring the realm of image processing techniques.
Video player with the function of improving the quality of the hand-drawn image using the high-performance scaling algorithm of Anime4K
A High-Quality Real Time Upscaler for Anime Video
Many algorithms for imbalanced data support binary and multiclass classification only. This approach is made for mulit-label classification (aka multi-target classification). 🌻
BEGANSing - Korean SVS + SVC + AudioSR
WindSR Dataset contains more than 22,000 pairs of HR/LR wind speed images, which are processed using the NASA's GEOS-5 Nature Run dataset. This dataset is useful for studying super-resolution for data collected using satellites rather natural RGB images.
Handy DSP routines
An implementation of SMOTE
NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Rates @ INTERSPEECH 2022
Nearly complete submissions for Super Resolution Convolutional Neural Network (SRCNN) algorithm.
This project aims to analyze diabetes data using data management, captivating visualizations, and cutting-edge machine learning techniques to predict the presence of diabetes in individuals. Our robust dataset includes comprehensive health exam results and family history.
Amazon employee data to predict approval/ denial
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