Popular GitHub Repositories for Histogram Equalization

Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.

This is a resouce list for low light image enhancement

Nerdlog: fast, remote-first, multi-host TUI log viewer with timeline histogram and no central server

White balance camera-rendered sRGB images (CVPR 2019) [Matlab & Python]

Reference code for the paper HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms (CVPR 2021).

PyTorch implementation of Data Free Quantization Through Weight Equalization and Bias Correction.

Control adaptive filters with neural networks.

The goal of this project is to solve the task of name transcription from handwriting images implementing a NN approach.

Python implementation of factorization based image segmentation algorithm

AI ML based Image enhancement module built in Python. It is used for improving the quality of images using different filters in openCV. It works better with gray-scale images.

Implementation of paper 'Two Step Approach for Single Underwater Image Enhancement'

Face recognition, Eigenfaces, Local Binary Pattern Histogram, Fisherfaces, opencv, pyqt.

An Tensorflow.keras implementation of Same, Same But Different - Recovering Neural Network Quantization Error Through Weight Factorization(https://arxiv.org/pdf/1902.01917.pdf) ---ICML2019

A one-shot method for selecting next best view for active object recognition

Code release for "Neural Histogram-Based Glint Rendering of Surfaces With Spatially Varying Roughness"

colab-tensorflow-tpu-example

Factorization based image segmentation algorithm

This repository tackles latent space misalignment in multi-agent AI-native semantic communications. It introduces a federated approach where an access point shares a semantic encoder, while user devices use local semantic equalizers to enhance mutual understanding.

Implementation of Fundamental Image Processing Techniques

This project comprises of hybrid model of LBPH, CNN and frontal_haascade model. Frontal Haarcascade is used for face detection from the image, LBPH(Local Binany Pattern Histogram) is used for face recognition and CNN is used for face mask detection system. mySQL database is used to store the records of employee, which is used while recognizing face. Flask framework is used to build front-end.