Face detection and alignment using deep learning

A flask app to give a demo of Facial Recognition - Deployed with Live Demo.

AI-powered safety monitoring system for industrial sites, detecting PPE compliance and unauthorized access in real-time with facial and object recognition.

Deploy face detection app using deep learning

A real-time facial recognition system using MTCNN for face detection, InceptionResNet for embedding generation, and FastAPI for a high-performance REST API. Built with PyTorch, it supports multiple camera feeds, making it ideal for surveillance, access control, and identity verification at scale.

Face Recognition Inception Resnet in Computer Vision

Face privacy protection using adversarial perturbations. MI-FGSM attack on FaceNet embeddings achieves cosine similarity < 0.5 with PSNR > 40 dB. 5/5 surrogate model transfer. Flask web UI.

Deep learning-based smart attendance system using FaceNet, MTCNN, and SVM for real-time face recognition and automated attendance tracking.

AI-Based Missing Person Identification System is a smart surveillance platform that uses AI, face recognition, and CCTV video analysis to identify missing persons. The system compares detected faces from uploaded videos with stored database images and helps police track and locate missing individuals quickly and accurately.

Face Detection using MTCCN Model in Computer Vision

Face detection web application. This application allows multiple users simultaneously to upload images for face detection performed by MTCNN model. The system outputs the predicted faces by sending JSON message from the server to the client with bounding boxes coordinates. Operations are asynchronous without the need to reload the webpage.

🎯 IDentix — A face recognition attendance system with real-time face detection (MTCNN + FaceNet), RTSP camera support, JWT-authenticated REST API, and a modern web dashboard built with FastAPI, PyTorch, and OpenCV.