We’re proud to release AIRealNet — a binary image classifier built to detect whether an image is AI-generated or a real human photograph. Based on SwinV2 and fine-tuned on the AI-vs-Real dataset, this model is optimized for high-accuracy classification across diverse visual domains.
If you care about synthetic media detection or want to explore the frontier of AI vs human realism, we’d love your support. Please like the model and try it out. Every download helps us improve and expand future versions.
We’ve just released our new dataset: **Bhagwat‑Gita‑Infinity** 🌸📖
✨ What’s inside: - Verse‑aligned Sanskrit, Hindi, and English - Clean, structured, and ready for ML/AI projects - Perfect for research, education, and open‑source exploration
🚀 New Release from XenArcAI We’re excited to introduce AIRealNet — our SwinV2‑based image classifier built to distinguish between artificial and real images.
✨ Highlights: - Backbone: SwinV2 - Input size: 256×256 - Labels: artificial vs. real - Performance: Accuracy 0.999 | F1 0.999 | Val Loss 0.0063