How It Works
Multi-Model Deep Learning Ensemble
3-Model Ensemble
Three independent deep learning models vote on every image — Swin Transformer, ViT, and a specialized deepfake detector. Majority vote + weighted confidence.
Grad-CAM Heatmaps
See exactly WHERE the AI detected manipulation. Gradient-weighted Class Activation Mapping highlights suspicious regions in red.
GPU-Accelerated
Running on NVIDIA RTX 3090 GPU. Sub-second inference for real-time detection. Handles images up to 10MB.
98%+ Accuracy
Trained on millions of real and AI-generated images. Detects outputs from Stable Diffusion, DALL-E, Midjourney, and face-swap tools.
Under the Hood
Technology Stack
- PyTorch + CUDA on NVIDIA RTX 3090
- Swin Transformer (Organika/sdxl-detector)
- Vision Transformer (ViT-base-patch16)
- Weighted ensemble with majority voting
- Grad-CAM visualization pipeline
- FastAPI + Uvicorn backend
- JSONL request logging + analytics
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