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Ai Vs Human Generated Image Detection
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Ai Vs Human Generated Image Detection

Developed by dima806
A Vision Transformer (ViT)-based image classification model for distinguishing AI-generated from human-created images, achieving 98% accuracy.
Image Classification
Transformers
Open Source License:Apache-2.0#AI Image Detection#High-precision Classification#Generated Image Authentication
Downloads 148
Release Time : 1/25/2025

Model Overview

This model uses Google's ViT architecture, fine-tuned specifically for AI-generated image detection tasks, efficiently identifying whether an image is AI-generated.

Model Features

High-precision Detection
Achieves 98% accuracy on test sets with an F1 score of 0.978.
Balanced Performance
Balanced recognition performance for both AI-generated and human-created images (recall rates >96%).
Modern Architecture
Based on the Vision Transformer architecture, outperforming traditional CNN methods.

Model Capabilities

AI-generated Image Detection
Image Authenticity Analysis
Binary Image Classification

Use Cases

Content Moderation
Social Media AI Content Labeling
Automatically identifies AI-generated images on platforms.
Reduces manual review workload by 98%.
Digital Forensics
Disinformation Detection
Identifies AI-generated images potentially used for false propaganda.
Accurately detects 96.5% of synthetic images.
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