Imagetwin

About Imagetwin

Imagetwin is an AI-powered software designed to detect image integrity issues in scientific research papers. Its core purpose is to maintain the quality and trustworthiness of scientific publications by identifying potential problems like duplication, manipulation, plagiarism, and AI-generated content. Imagetwin's key features include the detection of **image duplications** within a single manuscript or across multiple publications; **manipulations**, such as splicing, copy-move forgeries, and contrast adjustments; and **plagiarism** by comparing images against a large database of over 75 million published figures. A unique feature is its **AI-generated image detection** (in beta), which identifies synthetic images. The tool provides **confidence scores** for each analysis, a **forensic toolbox** for detailed evaluations, and the ability to create **private repositories** for auto-checking new submissions. Data is protected with **industry-standard encryption**. It also offers **API access**. Imagetwin is used by **publishers** to maintain journal credibility, **academic institutions** for research audits and misconduct investigations, and **researchers** to ensure figure integrity before submission. Its unique selling points include its comprehensive approach, AI-generated image detection (beta), speed, ease of use, and private repository availability. The tool supports PDF and various image file formats and integrates with publishing workflows via its API. Imagetwin's achievements include incubation in the TU Wien i²ncubator and funding from Austrian ministries. It has been featured in Science, Nature, and the Guardian. Recent updates include a beta feature for detecting AI-generated images, private repositories, and confidence scores.

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