a web in masked face recognition system for undergraduate final test (本科毕设：可遮挡的人脸识别系统）

Existing Face Recognition systems fail in recognizing the persons when they are masked but I have developed a face recognition system that is capable of recognizing persons even when they are masked with different kinds of occlusion such as Facemasks, templates, Handkerchiefs, and so on. I have even deployed my model using Streamlit.

MaskNet is an Occluded face recognition system which capable in recognition masked faces. The project is developed through a research study. the research study can found here. https://www.researchgate.net/project/Face-Mask-Invariant-Face-Recognition-with-Identity-Verification

Masked Face Recognition System

Masked-Face Recognition and detection system that can achieve real-time face recognition while wearing a facial mask.

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The world is currently under the impact of COVID-19. Wearing face masks has become mandatory for all. Face recognition systems have become inefficient as most of the face remains covered so it becomes difficult to identify the faces. With our project we aim to solve this problem by training our model with occluded faces. We plan to use CNN i.e. Convolutional neural networks to extract the features of the face and identify it.

Masked Face Recognition Based Attendance System using Deep Learning

Masked Adversarial Attacks on Face Recognition Systems

Update the original face recognition system into masked face recognition system when lose features caused by Mask.

A deep learning-based binary classification model using TensorFlow and Keras to detect masked vs. unmasked faces. Trained on a Kaggle dataset with 10,000 images, the model achieved 98% validation accuracy using the Inception ResNet V2 architecture. Includes data preprocessing, visualization, and performance evaluation.

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With the onset of the corona virus pandemic, the traditional face recognition systems have been rendered inadequate due to their inability of modeling and recognising accurately those people with face masks. This repository seeks to assist in such endeavours

This repository contains a Machine Learning project implemented in Python to detect faces with and without masks. The system leverages Haar Cascade Classifiers for efficient face detection and classification. It is designed to identify masked and unmasked faces in real-time.

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Face Recognition System : Face Detection, Mask Detection, FRS non-mask, Masked FRS

This project focuses on developing a robust face recognition system using thermal infrared images to identify masked individuals. By analyzing heat-based facial features from unoccluded regions, the system ensures reliable identification under low light, occlusion, and varying environmental conditions.

A comprehensive face recognition system that supports mask augmentation for improved recognition accuracy. This system uses deep learning models to register and recognize faces, with special support for masked face scenarios.

Machine Learning Algorithm to classify an input face from image, video or live stream to masked and unmasked face, this algorithm is sub algorithm of HumaneX Masked Face Recognition Pipeline prepared for HumaneX Eco System

AI-powered airport security system using real-time CCTV feeds for face detection and recognition. Identifies criminals, flags suspicious individuals, and tracks movement across cameras. Supports masked face recognition, alert system, and secure database integration for real-time monitoring.

In this face recognition project, a computer system will be able to find and recognize users masked face precisely in images or videos that are being captured through a surveillance camera.

The Masked Face Recognition System is an AI-powered solution developed during the COVID-19 pandemic to accurately recognize faces even when they are partially covered by masks. This system addresses the challenges of traditional facial recognition technology, which struggles with occlusions caused by masks.