There are 0 repository under downsampling topic.
A library for real-time voice processing in web browsers
High-performance time series downsampling algorithms for visualization
Bicubic interpolation for images (Python)
Official repository for paper "Attention-based Point Cloud Edge Sampling" (APES), Highlight@CVPR 2023
PyTorch implementation of Learning to Downsample for Segmentation of Ultra-High Resolution Images
Ansible role to setup downsampling with continuous queries on influxDB, optionally with backfilling and compaction of existing raw data.
The demo demonstrates downsampling images technique on the example of a UICollectionView based gallery with prefetching data.
Extended AsyncImage to perform down sampling when downloading image
MinMax-preselection for Efficient Time Series Line Chart Visualization (using LTTB)
Simple sinc interpolation in PyTorch.
Pointcloud-based frontier exploration using ROS, PCL and C++.
An algorithm that decimates a curve composed of line segments to a similar curve with fewer points.
Music spectrum analyzer implemented on a 7-series FPGA with novel DSP algorithms written in VHDL to accurately bin piano keys to frequency ranges and display in real-time
Collect data from Prometheus and downsampling
Native bindings to libsamplerate
A moiré-free image resizing script for Photoshop
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.
Gaussian/Laplacian Pyramids OpenCV
Largest-Triangle-Three-Buckets algorithm for downsampling time-series data while retaining original shape including sharp inflections
A custom processor implemented in Verilog HDL for image down sampling for UOM's EN3030 Circuits and Systems Design module ❄
Sliding window functions for processing iterative timeseries data in python.
Red neuronal para sub-muestrear espacialmente imágenes. Proyecto realizado para la asignatura de Inteligencia Artificial en la Pontifica Universidad Javeriana.
Original implementation of the Downsampled Diffusion Probablistic Models (dDDPM) in PyTorch, as part of my M.Sc. thesis on deep generative models.
The project was run in ROS and RViz simulation to practice 3D image segmentation and train a robot with SVM algorithm.
Collect data from Prometheus and downsampling
PICAFlow: a complete R workflow dedicated to flow/mass cytometry data, from data pre-processing to deep and comprehensive analysis.
Created algorithm in C to detect and highlight best image match with template (2 px accuracy) using pixelwise brute force. The algorithm is optimized by 16x to take less than 5 seconds per image-template pair on i7 processor by down-sampling.
image down-sampling technique using the Fast Fourier Transform (FFT) method in Python and MATLAB
Exploring texture image processing with the Kylberg Texture Dataset, this project involves preprocessing, learning-free classification, and a multilayer perceptron. Metrics evaluate performance and compare methods. It was part of my uOttawa Master's in Computer Vision (2023).