gaussian-noise
There are 35 repositories under gaussian-noise topic.
SonghyunYu/DIDN
Pytorch Implementation of "Deep Iterative Down-Up CNN for Image Denoising".
shivamsaboo17/Deep-Restore-PyTorch
Deep CNN for learning image restoration without clean data!
Mithilesh1609/QPSK-modulation-and-demodulation
This is Matlab implementation of modulation and demodulation of QPSK signals with added white Gaussian noise
antimattercorrade/Image_Denoising
Non Local Means (NLM) python implementation.
rbga/Low_Density_Parity_Check_LDPC_Codes_-_MATLAB_Simulation
LDPC MATLAB simulation using BPSK + AWGN modulation decoded using Sum Product and Min Sum Algorithm
shiranzada/pure-noise
Official implementation for "Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images" https://arxiv.org/abs/2112.08810
dr-mushtaq/Computer-Vision
This repository is related to all about Computer Vision - an A-Z guide to the world of Computer Vision. This supplement contains the implementation of algorithms, statistical methods, and techniques (in Python)
akawincent/Noise-Reduction-DSP
In this project, low-pass filters and Kalman filters with different window function designs are used to denoise speech signals polluted in the full frequency band of Gaussian white noise
mahmoudai1/image-processing-filters
Digital Image Processing filters developed by python using ipywidgets.
DEVANSH-DVJ/Video-denoising
Video Denoising using Low Rank Matrix completion
chandnii7/Corner-Detection
Program for Harris Corner Detection with non-maximum Suppression, HOG Feature Extraction, Feature Comparison, Gaussian Noise and Smoothing.
mohamadmomeny/Learning-to-augment-strategy
Learning-to-Augment Strategy Using Noisy and Denoised Data: An Algorithm to Improve Generalization of Deep CNN
Pythonista7/DnCNN-tf2
Using CNN to de noise images.
SayantanDutta95/QAB-denoising
Signal and image denoising using quantum adaptive transformation.
mohamadmomeny/Create-New-Data-Using-Denoised-Images
An Autoencoder Model to Create New Data Using Noisy and Denoised Images Corrupted by the Speckle, Gaussian, Poisson, and impulse Noise.
SayantanDutta95/De-QuIP-Denoising
Denoising by Quantum Interactive Patches
tom-uchida/Add_Gaussian_Noise_to_Point_Cloud
Add Gaussian noise to point cloud
m3gofriends/Advanced-Image-Processing-Course-Homework
National Taiwan Normal University 2020 Autumn - 1091 Advanced Image Processing Course Homework.
adityatripathiiit/Image_Denoising
Python implementation of the Non Local Means algorithm for Image Denoising
AdityaTheDev/ImageDenoising-Using-Autoencoders
I built a Denoising Autoencoder to remove noise from the image. Image Denoising is the process of removing noise from the Images The noise present in the images may be caused by various intrinsic or extrinsic conditions which are practically hard to deal with. The problem of Image Denoising is a very fundamental challenge in the domain of Image processing and Computer vision. Therefore, it plays an important role in a wide variety of domains where getting the original image is really important for robust performance.
electricalgorithm/vectofil
A GUI and API for Gaussian and pseudo noise addition, and filtering with vector-based filters: Basic Vector Directional Filter, Vector Median Filter, Distance Directional Filter.
kpetridis24/non-local-means
GPU-ported Non-Local-Means for accelerated image denoising
LefaRaleting/DigitalCommunications_Practical1
Develop a simulation platform1 for a BPSK, 4QAM, 8PSK and 16QAM communication system transmitting information over an additive white Gaussian noise (AWGN) channel.
MattiaCazzolla/Neuroengineering-project
Vocal Tract Segmentation project from the course Neuroengineering @ Politecnico di Milano
tom-uchida/Depth_Peeling_for_Point_Cloud
Depth peeling for point clouds.
arushi2509/Defense-Mechanisms-Against-Adversarial-Attacks-in-Computer-Vision-
Developed robust image classification models to prevent the effect of adversarial attacks
hoomanbing/Outlier-Detection-and-Removal-from-Multimedia
Detection and removal of specific types of outliers present in different data formats which includes detection and removal of contextual outliers from textual data using LOF, outliers from tabular numeric data using LOF, gaussian noise from image data using NLM.
Lefteris-Souflas/Census-Privacy-Analysis
Exploring US Census microdata, tackling privacy issues, and anonymization. Exercise A delves into quasi-identifiers, anonymization methods, identification risks, and differential privacy. Exercise B involves data loading, k-anonymity, histograms, adding noise for privacy, computing private averages, and analyzing privacy parameter impacts.
RamPrakash08/Exceptional_Point_Sensors
Specifically showed that eigenvalue variations under a perturbation are not a good measure of the overall sensor performance near an Exceptional Point.
the-pinbo/image-denoising
The standard approach to image reconstruction using deep learning is to use clean image priors for training purposes. In this project, we attempt to achieve denoising without using a clean image prior and yet, achieving a performance comparable to, or sometimes, even better than that obtained using the conventional approach.
ArturoEmmanuelToledoAguado/Img_Ruido
Program in Matlab R2021b that makes noise to different images.
halegchen/University-Projects
Course projects, capstone and individual studies.
Leehwajung/ImageAreaProcessor
Image Processing Course - HW3
reece-iriye/Exploring-Errors-in-Regression
Explored Machine Learning regression models of varying flexibility and how flexibility relates to MSE, Bias, and Variance in our predictions for MATH 4377: Math of Machine Learning. Visualizations of the Bias-Variance trade-off are included, and the project heavily relied on Spline Regression degrees of freedom for flexibility measuring.