Criminal Detection Using Machine Learning in Python 🚨

🔍 Revolutionizing Security with AI

I'm thrilled to share my latest project: a Criminal Detection System powered by Machine Learning! This system is designed to enhance safety by identifying and tracking criminals using advanced image recognition and behavior analysis techniques.

Key Features

1. 💡 Image-Based Recognition: Detects criminal faces with exceptional accuracy using CNNs (Convolutional Neural Networks).
2. 📊 High-Accuracy Models: Trained on diverse datasets to ensure robustness in real-world scenarios.
3. 🧠 Behavior Analysis: Integrates emotion and pose detection to analyze suspicious activities.

Technical Workflow

1️⃣ Data Collection and Preprocessing

1. Curated datasets with thousands of labeled images.
2. Preprocessing steps include augmentation, normalization, and resizing to ensure model generalization.

2️⃣ Model Training

1. Developed custom CNN architectures for facial recognition.
2. Leveraged TensorFlow and OpenCV for feature extraction and performance optimization. Achieved an accuracy of over 90% during validation.

3️⃣ Real-Time Evaluation

1. Integrated real-time detection pipelines for image and video inputs.
2. Optimized model predictions for low latency in live scenarios.
3. Impactful Use Cases
4. Enhances surveillance systems for law enforcement agencies.
5. Aids in tracking and identifying wanted individuals in crowded areas.

🚀 Let’s bring the power of AI to public safety! If you’re passionate about AI, I’d love to connect and discuss further.

📸 Some Screenshots of the Project 🖼️✨