Topic: cross-correlation Goto Github
Some thing interesting about cross-correlation
Some thing interesting about cross-correlation
cross-correlation,Python library to compute functional connectivity measures from EEG
User: 5a7man
cross-correlation,Fast Automated Spectral Extraction Software for IFU Datacubes
User: a-griffiths
cross-correlation,Cross correlation in Node.JS
Organization: adblockradio
cross-correlation,General purpose correlation and covariance estimation
User: aebilgrau
cross-correlation,A utility to find the best audio matches for videos and sync them together, perhaps for your films
User: alexscarlatos
cross-correlation,Audio tracks synchronization command-line tool for video editors that don't support it
User: alopatindev
cross-correlation,Golang library for comparing one time series with a group of other labeled time series
User: aouyang1
cross-correlation,Calculate rhythmic complexity of music from audio files, via onset strength cross-correlation
User: arnavlavan
cross-correlation,Custom CUDA kernel doing a normalized cross correlation on a batch of signals via pycu_interface.
User: asuszko
cross-correlation,Sobel edge detection implemented on PyTorch
User: chaddy1004
cross-correlation,Julia module for Detrended Cross-Correlation Analysis.
User: cnelias
cross-correlation,Seismic cross-correlation codes
User: core-man
cross-correlation,JayBeams: A Project to have fun Coding, and maybe measure relative delays in market feeds
User: coryan
cross-correlation,OSSA (Open-Source Sorting Algorithm) is an interactive software for manual curation of neural spikes.
User: delunapaolo
cross-correlation,Earthquake detection and analysis in Python.
Organization: eqcorrscan
Home Page: https://eqcorrscan.readthedocs.io/en/latest/
cross-correlation,A Python GUI for Digital Particle Image Velocity (DPIV)
User: erichzimmer
cross-correlation,Bat like sonar sensor that can track multiple targets and estimate angle of arrival using chirps and cross correlation in near real time.
User: filipmu
cross-correlation,:bar_chart: Visualization of flow structure in cylinder
User: foroozani
Home Page: https://github.com/Nek5000
cross-correlation,A Particle Image Velocimetry (PIV) code in Python and Matlab
User: forughi
cross-correlation,Synchronization tool for videos of the same event. Uses audio cross correlation to synchronize.
Organization: freemocap
Home Page: https://freemocap.github.io/skelly_synchronize/
cross-correlation,PerHealth'21 - PulSync: The Heart Rate Variability as a Unique Fingerprint for the Alignment of Sensor Data Across Multiple Wearable Devices
User: fwolling
cross-correlation,ABC (AmBient noise and Coda) is to compute cross correlation time functions from ambient noise or coda.
User: geophydog
cross-correlation,Fourier analysis applications for image matching.
User: gkalliatakis
cross-correlation,This repository will contain necessary signal processing codes in Matlab or Python of my course " Digital Signal Processing (CSE3132) ".
User: h-k-r
cross-correlation,Acquire bright field images along with the super resolution data and use it to track drift in 3D with nanometer precision!
Organization: imodpasteur
cross-correlation,Noisy Dispersion Curve Picking
User: ivangch
Home Page: https://github.com/IvanGCh/NDCP.git
cross-correlation,Collide, Collate, Collect: Recognizing Senders in Wireless Collisions
User: jlauinger
cross-correlation,Ambient Noise Cross-Correlation in Julia
Organization: juliaseismo
cross-correlation,Explores cross-correlation between time series of internet search term frequency and subsequent stock losses.
User: matthewebates
Home Page: https://github.com/matthewebates/financial_data_analysis
cross-correlation,Proposed to develop a low-communication cost cross-correlation method with the idea of Compressed Sensing
User: meowoodie
cross-correlation,Seismic Ambient Noise Two-Station Interferometry
Organization: noiseciei
Home Page: https://ds.iris.edu/ds/products/ancc-ciei/
cross-correlation,Seismic Ambient Noise Cross-Correlation in Parallel
Organization: noiseciei
cross-correlation,FFT and IFFT for `vector`, with minimal dependencies
User: ocramz
cross-correlation,Interactive Semi Automatic Image 2D Bounding Box Annotation and Labelling Tool using Multi Template Matching An Interactive Semi Automatic Image 2D Bounding Box Annotation/Labelling Tool to aid the Annotater/User to rapidly create 2D Bounding Box Single Object Detection masks for large number of training images in a semi automatic manner in order to train an object detection deep neural network such as Mask R-CNN or U-Net. As the Annotater/User starts annotating/labelling by drawing a bounding box for a few number of images in the selected folder then the algorithm suggests bounding box predictions for the rest of the yet to be annotated/labelled images in the folder. If the predictions are right then the user/annotater can simply press the keyboard key 'y' which indicates that the detected bounding box is correct. If the prediction is wrong then the user/annotater can manually draw a rectangular 2D bounding box over the correct ROI (Region of interest) in the image and then press the key 'y' to proceed further to the rest of the images in the folder. If the user/annotater made a mistake while drawing the 2D bounding box, then he/she can press the key 'n' in order to remove the incorrectly marked 2D bounding box and he/she can repeat the process for the same image until he/she draws the correct 2D bounding box and then after drawing the correct 2D bounding box, the user/annotater may press the key 'y' to continue to the rest of the images. The 2D bounding box prediction over the whole image data set improves as the user/annotater annotates/labels more number of images by drawing 2D bounding boxes. This tool allows the user/annotater to not only interactively and rapidly annotate large number of images but also to validate the predictions at the same time interactively. This tool helps the user/annotater to save a lot of time when annotating/labelling and validating the predictions for a large number of training images in a folder. Instructions to use:- 1. If the training images are in JPEG or any other format, then convert them to PNG format using some other tool or program before using these images for annotation. 2. All the training images must contain the object of interest which is to be annotated. 3. Currently the application only supports 2D bounding box annotation for single object detection per image, but in the future semantic segmentation based annotation features will be added which will allow precise boundary segmentation masks of an object in an image. 4. If some or all of the training images have varying dimensions(shapes/resolutions), then resize them to the same dimensions using this tool by providing the height and width to which all the training images need to be resized to. The height and width are inputed separately in two different dialog boxes which pop up once the program is executed. If the training images need not be resized then press the cancel button in the dialog boxes requesting the height and width. 5. Select the folder containing the training images by navigating to the folder containing the training images through a dialog box which pops up after the program is executed. If the images need to be resized then two dialog boxes pop up. The first dialog box is to navigate to the destination folder containing the unresized raw training images and after resizing another dialog box pops up to navigate to the folder containing the saved resized training images named as "resized_data". If the images need not be resized then only one dialog box pops up so that the user can navigate to the raw training images folder directly. 6. The images in the folder pop up one by one. After drawing the correct 2D bounding box over the ROI (region of Interest), press the 'y' key. Except the first image, the rest of the images will have a 2D bounding box drawn over them. If the predicted box is accurate, then continue by pressing the 'y' key. If the prediction is incorrect, then draw the accurate bounding box and press the 'y' key. If any mistake occured while drawing the 2D box, then reset the image by removing the incorrect drawing by pressing the 'n' key and then draw the correct box and press the 'y' key. 7. The output images are stored in four different folders in the same directory containing the training images folder. among the four folders, one contains the cropped templates of the bounding boxes, black and white mask images, training images and the images with 2D box detection markings.
User: robertarvind
Home Page: https://github.com/robertarvind
cross-correlation,Python implementation to calc mappability-sensitive cross-correlation for fragment length estimation and quality control for ChIP-Seq.
User: ronin-gw
cross-correlation,This is a repository where I added my DSP codes that have written in Matlab (without built-in function). I have also commented inside every code so that it will become helpful for newbies. Also added cross-check using Library Function.
User: saifergit
cross-correlation,Real-time GCC-NMF Blind Speech Separation and Enhancement
User: seanwood
cross-correlation,Particle Image Velocimetry for Matlab, official repository
User: shrediquette
Home Page: https://shrediquette.github.io/PIVlab/
cross-correlation,An enhanced implementation of the ccf cross-correlation function
User: sigurdjanson
cross-correlation,Cross correlation tools for R
User: simonvaughandataandcode
cross-correlation,A computationally efficient earthquake detection module for SeisComP
Organization: swiss-seismological-service
Home Page: https://scdetect.readthedocs.io
cross-correlation,spatial and temporal cross correlations in 1D and 2D for fluorescent microscopy (ImageJ plugin)
Organization: uu-cellbiology
cross-correlation,This repository include all the codes and constraints used in the development of the Master Thesis: "Development of a Differential Absorption Lidar System based on a SoC-FPGA for Carbon Dioxide Sensing" by Victor Ricardo Aguilera Sanchez
User: victorricardoaguilerasanchez
cross-correlation,First implementation of the audio synchronization feature for Vidify, now obsolete
Organization: vidify
cross-correlation,a Python code for mechanical Digital Image Correlation (DIC) using numpy & scikit-image
User: xdze2
cross-correlation,My ongoing project on understanding the neural correlates of memory formation involving statistical analysis of information flow between different sub-regions of hippocampus (EC, DG, CA3, and CA1)
User: yash-shashank-vakilna
cross-correlation,Matched filter earthquake detector
User: yijianzhou
cross-correlation,Calculate videos cross-correlation by their audio
User: yoavain
cross-correlation,Matlab GUI for uREPET, a simple user interface system for recovering patterns repeating in time and frequency in mixtures of sounds.
User: zafarrafii
Home Page: http://www.zafarrafii.com/
cross-correlation,Cybervision can generate a 3D model from two photos of an object
User: zlogic
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