GRU Model That uses a sequence of MobileNet Image Features to classify a video clip as class label shoplifting or not shoplifting.
This is Embed-C code written in Arduino IDE for ESP8266 for a "Low-Cost Theft-Detection System using MPU-6050 and Blynk IoT Platform".
Aisle Guard is a lightweight, end-to-end computer vision system for detecting and logging potential shoplifting events from retail camera footage.
AI based website for real time montoring natural resources.
AI Surveillance PWA for real‑time theft detection using YOLO, OpenCV, Flask, Socket.IO, RTSP recording, and alerting.
An AI-powered system for automatic shop theft detection using deep learning and computer vision. Supports multiple video classification models (EfficientNet + LSTM, 3D CNN, Transformers, VideoMAE). Uses YOLOv8 to detect people in frames. Deployed with a Django web app for easy video upload, prediction, and annotated output.
Real-time AI-powered theft detection system for retail. Detects shoplifting, concealment, and suspicious behavior using YOLOv8 & Computer Vision with a modern web dashboard.
👁️ Detect and log potential shoplifting events with Aisle Guard, a lightweight computer vision system for analyzing retail camera footage.
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