Easily run mpd with Alsa or PulseAudio output with Docker. Upsampling 2x 4x 8x with "Goldilocks" settings by Archimago. Scrobbling support.
Easily run SqueezeLite with Alsa or PulseAudio output with Docker. Bluetooth support. Upsampling 2x 4x 8x with Goldilocks settings by Archimago
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.
GUI application for Anime4K shaders which allows to save upscaled video to disk
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
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.
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
The objective is to build various classification models, tune them and find the best one that will help identify failures so that the generator could be repaired before failing/breaking and the overall maintenance cost of the generators can be brought down.
Upsampling already available land cover raster layers using machine learning inside Google Earth Engine platform.
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